{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"http://hilpisch.com/tpq_logo.png\" alt=\"The Python Quants\" width=\"35%\" align=\"right\" border=\"0\"><br>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Python for Finance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Analyze Big Financial Data**\n",
    "\n",
    "O'Reilly (2014)\n",
    "\n",
    "Yves Hilpisch"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img style=\"border:0px solid grey;\" src=\"http://hilpisch.com/python_for_finance.png\" alt=\"Python for Finance\" width=\"30%\" align=\"left\" border=\"0\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Buy the book ** |\n",
    "<a href='http://shop.oreilly.com/product/0636920032441.do' target='_blank'>O'Reilly</a> |\n",
    "<a href='http://www.amazon.com/Yves-Hilpisch/e/B00JCYHHJM' target='_blank'>Amazon</a>\n",
    "\n",
    "**All book codes & IPYNBs** |\n",
    "<a href=\"http://oreilly.quant-platform.com\">http://oreilly.quant-platform.com</a>\n",
    "\n",
    "**The Python Quants GmbH** | <a href='http://tpq.io' target='_blank'>http://tpq.io</a>\n",
    "\n",
    "**Contact us** | <a href='mailto:pff@tpq.io'>pff@tpq.io</a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Statistics (a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pylab import plt\n",
    "plt.style.use('ggplot')\n",
    "import matplotlib as mpl\n",
    "mpl.rcParams['font.family'] = 'serif'\n",
    "# import warnings; warnings.simplefilter('ignore')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Normality Tests"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Benchmark Case"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "uuid": "b5c2a3e0-81d2-4aab-bee0-a9239fc9ffa6"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/yves/miniconda3/envs/py4fi/lib/python3.6/site-packages/statsmodels/compat/pandas.py:56: FutureWarning: The pandas.core.datetools module is deprecated and will be removed in a future version. Please use the pandas.tseries module instead.\n",
      "  from pandas.core import datetools\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "np.random.seed(1000)\n",
    "import scipy.stats as scs\n",
    "import statsmodels.api as sm\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "uuid": "596ccb67-e163-4f15-95e8-80362bdade98"
   },
   "outputs": [],
   "source": [
    "def gen_paths(S0, r, sigma, T, M, I):\n",
    "    ''' Generate Monte Carlo paths for geometric Brownian motion.\n",
    "    \n",
    "    Parameters\n",
    "    ==========\n",
    "    S0 : float\n",
    "        initial stock/index value\n",
    "    r : float\n",
    "        constant short rate\n",
    "    sigma : float\n",
    "        constant volatility\n",
    "    T : float\n",
    "        final time horizon\n",
    "    M : int\n",
    "        number of time steps/intervals\n",
    "    I : int\n",
    "        number of paths to be simulated\n",
    "        \n",
    "    Returns\n",
    "    =======\n",
    "    paths : ndarray, shape (M + 1, I)\n",
    "        simulated paths given the parameters\n",
    "    '''\n",
    "    dt = float(T) / M\n",
    "    paths = np.zeros((M + 1, I), np.float64)\n",
    "    paths[0] = S0\n",
    "    for t in range(1, M + 1):\n",
    "        rand = np.random.standard_normal(I)\n",
    "        rand = (rand - rand.mean()) / rand.std()\n",
    "        paths[t] = paths[t - 1] * np.exp((r - 0.5 * sigma ** 2) * dt +\n",
    "                                         sigma * np.sqrt(dt) * rand)\n",
    "    return paths"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "uuid": "7b6ba027-7f3c-43ee-a297-66599a4c9ac2"
   },
   "outputs": [],
   "source": [
    "S0 = 100.\n",
    "r = 0.05\n",
    "sigma = 0.2\n",
    "T = 1.0\n",
    "M = 50\n",
    "I = 250000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "uuid": "abdf423c-dc32-4528-8781-12e05a6703cd"
   },
   "outputs": [],
   "source": [
    "paths = gen_paths(S0, r, sigma, T, M, I)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "uuid": "133e6168-692d-4aa7-8b8d-81d21e1d21e9"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'index level')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYwAAAEMCAYAAADXiYGSAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMS4wLCBo\ndHRwOi8vbWF0cGxvdGxpYi5vcmcvpW3flQAAIABJREFUeJzsnXd8FGX6wL/v7G42vfdKIEDoNXSk\ndxBFXbvoebaf7Sxn76ee58mpZy8n9rKCqKB0IfQWSmihJpDee9sy7++PxUhIAkkIKTjfz2c/hJl3\nZp53d2aemacKKSUaGhoaGhrnQmlrATQ0NDQ0OgaawtDQ0NDQaBSawtDQ0NDQaBSawtDQ0NDQaBSa\nwtDQ0NDQaBSawtDQ0NDQaBSawtDQ0NDQaBSawtDQ0NDQaBSawtDQ0NDQaBT6thaghdHS1jU0NDSa\njmjMoItNYZCRkdGs7fz9/cnLy2thado32pwvfv5s8wVtzk0lNDS00WM1k5SGhoaGRqPQFIaGhoaG\nRqPQFIaGhoaGRqPQFIaGhoaGRqPQFIaGhoaGRqPQFIaGhoaGRqPQFIaGhoaGRqPQFIaGRhORCZuQ\nOc3L99HQ6MhoCkNDownIzFTU919BXfhZW4uiodHqaApDQ6MJyGU/OP7Ym4CsqmxbYTQ0WhlNYWho\nNBJZkIvcuhaiu4HVgty7o61F0tBoVS66WlIaGhcKufInAJTbHkZ95RHkjo0QN7qNpQJZXobcvBpU\nFXQG0OsdH50eS3QXZGA4QjSqtpyGxlnRFIaGRiOQpSXIdcsRQ8YgAoIRA0cgN61CVlchjM5tKpv6\n+Vuwc3O96woB8deHEEPHtK5QGhclmsLQ0GgEcs0SsFQjps4BQAweiVz7KzJxByJuVNvJdWgv7NyM\nmHUNYtJlYLOB/dTHakX3xdtYv/0I2XMAwsOzzeTUuDjQfBgaGudAVlUif/sF+g9FhEY6FnbtCZ7e\nyIQNbSeXakf99mPwDUBMvQLh4orw8ER4+yL8AhHBYXj+32NQWY78/n9tJqfGxYOmMDT+FEgpSSup\nRsraPbZkVQX2d19GNmDSAZAbVkB5KcrUK2qWCUWHGDgc9u5AVle1qKxl1XYO5VViU8/eD0xuWAlp\nyYgrb0Y4Gesdo4/qgph6BXLzGuSBXS0qp8afD01haFz0VNtUXt+Uyd2Lk1mYmFlrnUzYBLu2OHIr\nVv5UV6HYrMgVP0H3PogusbXWiUEjwWKBFoyWyi6z8MDSFB5ZfoKbFh5h3oYM1qWUUFZtry1XRTny\nx68gpidi8NlNYmKGCYLDUL94t8WVm8afC01haFzU5JZbeXzlCdallBDkbuCDTSfIr7DWrJdb1kJA\nMAwYjjT/D/nNB0j7HzdnuTUeCvNqvV3U0K0XeHg5oqVagMxSC0+uPEm51c5dQ4IYGu7Bnqxy5m3M\n4MaFR3hy1UlWHytyyPXLd1BWgnLNX88ZASUMTig33gN52cifv2kRWTX+nGhOb42Lln3ZFby6Ph2r\nKnliTBgRXkbu+yWZ/yXk8MjoMGRhPhzai5hxNWLWNciFnyFXLELm56Lc9jA4GZHLFkJENPQaUGf/\nv5ul5OY1yOpqhLF+s1CVTUUR4KRr+Pkso8TCU6tOYrGrvDghks6+zkztCnZVciS/iu3pZWxJLeW/\nW7IwlhczfPUSxIgJiKiYRn0XolsvxCVTkCt/Qg65BBHVpXFfoka74URRNWUWO70CXdtMBu0NQ+Oi\nQ0rJL4cKeWb1SdyNOv49NYoh4R6EeDgxd0gEG0+WkpBehty+DqREDB2DUBSUq25BXHcn7E1A/ffj\nyPilkJWOmHZlg0/xDrNUNeyrbZYqqbaz6lgRL6xJ5frvj3DLD0f5cncuRZW2OvtIK67miVUnsaqS\nf0yMJJoyZFIiUlXRKYLYABdu7B/AmzOi6ebnzLt7isl180dcfmOTvhdxxVzw9Eb9/K1ab1Ea7Z/i\nKhtPrzrJM6tPcjiv7SoM6J577rk2O/gF4LnS0tJmbejq6kpFRUULi9O+uRjnXG1TeXdbNgv25zM4\nzJ1nxoXj72qoWT84OohVh7LZnl7GxJ0L0fv4oUy/sma9iO6KiOqCXLccdm+FgGCUG+5CiAaerXwD\nkPHLwFJNaZ9h/Ha8mC925/LB9my2ppVhVyXjOnvh7qRjxdFilhwqJK/CRqinE55GHSeLq3lq1Ukk\n8OLESKKqclFffRy55hfkljVgtUBQKMLojCIEvUtTWJoFh6MGMm5ANMo5zFGn/8bC4ITwD0SuXgzO\nLoiYHuf1XcvcLOTureDuiXBpu6feM7nYzmspJW9uySKlqAovo57NqaWMi/bCqP/jnDyfOXt4eAA8\n35ixmsI4xcV2kjWGi23OR/OreH5NKnuyKri6jx93DQmudVEBeLi74e9kY3FSIZQU0W9oX0Tn7rXG\niKAwRK+ByGNJKJfdgAiLavCYQlEgJ4uqXVt5wDaA+BOl6IRgcow3tw4KYu6AAAaGujMqypPRnTyx\n2CW/HXcojuOFVZj35qMIh7KIKM1AnfeUY79X3gJF+bBhpeMGn3ES3D1x+/4j/KqLWeLeE70i6BV0\n9hv1mb+xCIlApibD+hXg7AqhEQi94Sx7+ANZUeaIClu1GPW7j5CLv4HdW5H7dyKGjUMYGrefC83F\ndl6vP1GKeV8+1/cL4Ipefiw5VMiJompGRXnWvPm2lsIQZ0aFdHBkRkbzyk77+/uTl5fXwuK0by6W\nOdtVycL9+Xy7Nw8vZz33Dw+hf4hbvWN/n/Pr325gg9Wb18cFERkecF7Hlwf3sMi8ks9iZvLkmDDi\nwtzP6ogurLSx5FAhS48UYtQp/GNiBGEFJ1FffxaMzigP/gMRHObYd2YqMn4ZctNvUFkOgLjzcV6v\nimLDiRJemRxFd3+XBo9V328siwpQP/gXHD0ILm6I0ZMR42ci/Gp/D9Juh+TDyP27HCG5yUdAqmB0\ngdg+iJ79wc0DOf8N6DkA5Z4nEYquuV9ji3GxnNcABZU27l1ynFAPJ16ZHIVOESw5VMBHO3KYOyCA\nOT39gPObc2hoKECjasdoTm+NDk1GiYU3NmdwKK+K0VEe3BEXjIfx7DctqarM3fsdO2L/ynsHKng5\nTNZ7gy+qtOHprDun2ae8Uw8WdrIzwJbDkPDYs44F8HHRc2P/AEy9/bBLicuJw6j/fR5c3VEeehER\nEFwzVoREIK65DXn5TQ6fS1kJYuAw7rSqJOVWMm9jBm9M74SrofE3auHti+7RfyGPH0Ku+hm56ifk\nqp8QA0cgRk9G5mUj9++CpD1QUQ5CQKeuiBlXIXr0h87dEfo/bh1qRTny6/eRP36JmDO30XJonB0p\nJe9uzcRil9w/IgSd4jgPZ3TzYX9OJV/szqW7v0urOsE1haHRIZFSsuxIEfN35qDXCR4aGcolnRpZ\n+uJYEl45J5h7SSXv5BpZfbyYiV28qbap7M+pYGdGOQkZ5WSUWpjZ3YfbBgeddXc/HS6mTO/K9Xs+\nRVqGNphEdyZGvYI8tBf1rX+Aly/KQ/9A+Nb/tiOMRsSoSTX/d3PS8eDIEJ5YeZIPtmXzwMjQxs39\n9H127o64/e/I/JuRa5Yg161A7jiVue7thxgwHHoNRPTsh3DzaHg/Y6dBWgpy6ULUsE4oWt2qFuG3\n48VsTy/n1kGBhHv+cU4JIbhnaDDJhVW8tiGD16d3wr+VZNIUhkaHZOWxYt7fnk3/YFfuHR5Sy7F9\nLuTWteDkxIRL+vDb+jw+3ZnDppOl7M2uwGKXOOkEvQNdCfN0YsmhQgaEuDE4zL3efRVV2vjpYAGj\nvO10LkxB7twEQy5p0DQjpYTSYshMRZ446ki+8w9ymKG8fZv0HfQIcOXqPv58k5jHgFA3xkZ7NWn7\n3xF+AYgrb0HOvAb274LgcIdvo5EVboUQcO1tyKxU5GdvIYNCEZ26NksWDQe55VY+TsihV6ALM7v7\n1Fnv5qTj0dFh/H3ZCf6zMYO3rjr7Q01L0WoKw2QyBQMvAv3MZnPcqWWPAsFAFjAIeMZsNiedWncD\nMACwA8fMZvMHrSWrRvtGlZIfDxYQ4+vMs+MjzmkyOh1ptSJ3bET0H4bi4sZdQ/T8fVkKmaUWJsd4\nMzDEjd5Brhj1Cla7yt+Xn+DNzZm8OSMaX5e6l4t5Xx5WVXLdyM6w2gv5v9eR898Eb1/w8Uf4+IOP\nH1RXIzNPQmYqlJ0WmBEVg3L/swiP5t3sr+rlx+7Mct7ZmsWBnEqmdPWmi2/zqucKZxcYNKJ52+oN\nKHc+hvrSQ6jvvIzy5LwmK0ANB1JK3tqSiSol9w0LafD8jvZx5va4IN7ZmsVn21K5NObCm6ZaMw9j\nFPATtZ0r7sCDZrP5X8BC4N8AJpMpHHgYeNhsNj8C/NVkMmmPLBoA7MooJ73EwqWxPk1SFgDVu7ZA\neWlNue8obyNfm7rx3qVduG1wEIPC3Gsiqww6hQdHhlJlU3lzs+MCPp2sUgvLjxYxqYs3Yd4ujreE\n6+9CTL0S0b2vI/EvLdnhtN6xwZHzMWA44upbUf72PMq/PnHcWJupLAB0iuCR0WGMivJkTXIxDy5N\n4aGlKaw4WkSlVW32fpuD8PBCuedJqCxHffdlpNXSqse/WFhyqJA9WRXcPCCQYA+ns46d1MWLsdGe\nLNmf3Sq/d6u9YZjN5gUmk2nsGcuePu2/ClB26u8pQILZbP79Ct0MTAOOXGg5Ndo/Px8qxNdFz4jI\nuj4LeWgv6vw3EVPnIMZMq2NWqVq3Atw9oecfmdt6pWGlE+ll5NZBgby3LZufkwq4rIdfzbpvEvNQ\nhODqPo5lIrwTIrzTec6u6fi6OCLDbh0UyNrkYpYfKeKdrVl8kpDDpX3KuDrWo8ZheqER4dEof/kb\n6nuvIBd/i5hzU6sc92Kg2qYyf2cOS48UMSjUjaldvc+5jRCCu4YE4+bpg72i+ILL2C58GCaTyQmY\nC9x9alEgcHpCRcmpZfVteztwO4DZbMbfv3nuH71e3+xtOyodcc7J+RXszizn9uFRhASdEQZaXU3+\nl+9CcQHyq/cxHNiN5z2PozvlSFYrysndvgGXCTPxDA6ub/f1cr2fH/vzrXyxO4/R3cPoHujO0dxy\n4lNKuG5QGN0jQ1p0js3FH7g5NIi5IyR7M0v5fncG3+3KIC6yJ8M7taJ5aPKlFG6Nx75zE363PdDq\n3f464nmdUlDBM6uSOJZfwbUDw7hjRBSGs5SSORO9Xo+tCX685tLmCuOUsngPeNJsNh87tTgHOL1I\njidwtL7tzWbzh8CHp/4rmxuLfDHFbjeWjjjnL7Zm4aQTjAo11JFd/eFzZFY6yoP/QGalY1nwCXn3\n3eDI1B48CnXjarBUU91vaJPnfdsAP/ZnlPDUkgO8Pr0Tb29Ix9WgMC3atV1+h6FOcNcgXzanFLD6\nQAZd3VvXPKX26IfcuZm8fbsRIRGteuyOdF5LKVl1rJiPdmTjrFd4Zmw4g8LcKS4saNJ+WiAPo1G0\naS0pk8nkAnwA/MdsNieYTKbfS4IuBwaZTKbfH02GA0vbQkaN9kNJtZ01ycWM6eSJl3PtZx2Zloxc\nschRkK9HP5Rx01GefgMCQ1A/eBX143nIDSvRBYXCGZndjcHTqONvI0LILLXwwppUtqeXM6en3zlz\nPtoSJ51CXKQP29PL6pRtv9CIvnEAyD3bWvW4HYlyi53XNmbw9tYsuge48MaMaAY1EI3XXmg1hWEy\nmcYANwIhJpPpqVPK4itgJPCOyWRaCzwGYDab04DXgNdNJtM84GOz2az5L/6ESNWOLCsBYMXRIix2\nyaxY3zpj1M/fcWQtX3VLzXIRHI7y6L8Ql16H3L4ejh7A+ZIpzTaR9A1244pefuzPqcTHWcfM2Lrh\nju2NkdE+5FXYSC6sbtXjCt8AiIhGJm5v1eN2JF5Yk8amk6Xc2C+A58dH1BuF195oTad3PBB/xuI5\nZxn/JfDlBRVKo10j00+gfvpfSE3Gfu3t/JofQ79gV6K8ayfGyfhlkHwYcesDCPfajnCh0zlKl/cZ\nhFy9BJepl1F1HtaZa/v6U1xlY0i4O8769l/seUQnXwSwPb2Mzs0Mt20uom8c8tcFyLKSOr9LR0WV\nkm1pZfQNdm1Sdv2ZZJZaSMqr5OYBAVze0+/cG7QT2v8Zr/GnQ9qsqIu/Rf3HA5CXDZ27sXnFRvIr\nbcyMqX3jkYX5yB8+h579EUPHNrhP0akryq0P1DjAm4teEdwzLIQh4Q1nPrcnfN2c6OrnzPb0snMP\nbmFEvyEgVeS+hFY/9oXim8Q8/rkunf9uzjwvM9+WVEdMz4jIjnEe/Y6mMDTaFfLEUdSXHkL+/DVi\n0AiUF95BefgllvSeTUhFHgO+ehFZ8IdzT/3mA7DbUa6/q9WjcdozsqwEdctayszziQt15Uh+FYX1\n9OK4oETFgKc3JLZcC9u2JD65GPO+fMI8ndicWkZ8Skmz97U1rYzOPkaC3M+eZ9HeaP9GM40/BdJq\nQS7+Frn8B/DwRrn7CUT/YQAcyqvksOrObdECZU8q6osPoNz5KJSXwa4tiDlzEYHtI7S1rZBSQkYq\nMnG7w29wLAmkSjkQd2cEX+HMjvQyJsWcO7a/pRCKgugzGLlzM9Jmq1WwsKORlFvJW1uy6BXowrPj\nInj2t1Q+3J5N7yDXJpWlAUc5maTcSq7p27FCf0F7w9BoJ8ifv0EuXYAYPh7l+bdrlAXA4qQC3AwK\nE8YMQHni3+Dqjvqfp1E/ewvCOyEmzW5DydsedfsG1MdvQ33uHuQPn4GlCjHjKpSHXwZFR2RKIv6u\n+rYzS1WWw5H9rX7sliKnzMrL69Lwc9Xz2OgwjHqF+4eHYJeSt5phmtqWXoYEhoW374io+tAUhka7\nQO7dAT36odx8H8LtjwspvcTCxpOlTIrxxsWgIEIjUZ54DXoPgqpKlBvv7tBPrueDVO2oCz5Ffvgq\neHghbrwb5dX56J5+A2X29YjuvTHExMKRfcSFubM7sxyLvXXzMejRD/QGZAc1S1VY7bwYn4bNLnlq\nbDiep8K5QzycuGVgILuzKlh6pKhJ+9ySWkqQu6FO8EZH4M95pWm0K2RJETL9BJmDJ5GSUkJKUTXJ\nhVUkF1ZTUGlDJ2B6tz9MKcLVDeXuJ6Gi7Kxlty9mZHkp6kevwf5diLHTEFf/td7OeYbeA7H+9DVx\ngU4sPSJJzKposPLuhUA4O5otycRtSNNfOpSfya5K/rMxk9Tiap4ZF0GEV+0b/JQYb7amljF/Zw79\ng90I9Ty3P6LCamdPVgUzunl3qO/id7Q3DI02Rx7ax6LIsdxT3I3XNmaw6EA++RU2+ga78peBgfxn\nWqc6zkEhRIdRFjL9hKMtagvuT33pIUja63iruP6uBtusOvUZCHY7vUtP4KwXbWOW6jsEcjIhK73V\nj30+fLE7l+3pZfx1UBAD6ungKITgnmHBOOkEb2zOwK6e2zS1K6McmyoZGtExzt0z0d4wNNoceSiR\nFaHD6eHvzO1xwUR4OTWpjk57RlZVOvp0l5UiZpgcn/Mwocmdm1A/eQOcXVAefgkR0+Os4w3d+4BO\nh+FIIv1DJrA9vYw7Zf0dBi8Uom+coyNf4nZESHirHbe55FdY+V9CDhtPljKtqzcz6ulH8Tt+rgbu\niAtm3sYMFh0o4MreZ8+p2JJahqdRR+xZ2uq2Zy6Oq1KjQ3MsJYscZx8mdPGms6/zRaMsAOSaXxwN\nk3oNQC75FvXVx5DZzes7ry5fhPreKxAaifLUf86pLAAUF1fo1BV5yOHHyG+LrG+/AAjvhExs32VC\n7Krk18OF3LMkmW1pZVzf1/+c3RYBRkd5MDLSg2/25nK8oKrBcVa7ZEdGGUPC3VutenBLc/FcmRod\nElmYz1YlCAXJ0A4YNXI2ZEU5ctkP0GcwuvufRdz+CGRnoL5wP+q65U2KrlFXL0EumI8YPArl7/9E\neDc+O1h06w0pRxjkp6/J+m5tRN8hcPQgsrz03IPbgJTCKh5bcYIPtmcT4+fMWzOjMfXxb9SNXQjB\nnUOC8XDS8ebmTKwNBBbsy6mgwqoyrIMkfdaHpjA02hR5KJHN/r3p5aXURKBcLMhVP0NFGcrs6wFQ\n4kahPPtf6BKL/OId1HdeQpaeu4eBun4F8tsPof9QxK0PIgxNi/sXsX1AVfFOO9yGWd9xoKrIfTub\ntJ08cQx59MAFkgqsdpXPduXw4NIUssqsPDAihBfGRxByjsZFZ+Jp1HH30BBSiqr5dm9+vWO2pJbi\nrBf0Db7wnfEuFJrC0GhTUpOOke4WxPCu51eyo70hy0uRq36CgcMRUV1qlgtff5S/PY8w3Qr7d6I+\n83+o8cuQqr3e/ahb45FfvAO9BqDc/kjz/B9deoBOhzy0l7hwd47kV1HQ2lnfnbqChxc0onqtlBJ5\naC/2159BffEB1FefQN20usVFqrapvByfzg8HChjX2Yt3ZnVmbLRXs/07ceHuTOzixQ8H8jmUV1lr\nnSolW9PKGBDyR0fHjkjHlVzjomBTAQgpGV5P97zWQNqsDvNQRcs+dcvlixx5IpdeV2edUBSUSbNR\nnnoDQqOQX76L+uKDyCO1n6Tlzk3IT16Hbr1R7nqiyW8WNcczOp/yY+xlyKmQ2h2t/JYhFAXRdzBy\n/06krX5lJaVEJm5H/dejqK89CWkpiDlzHWG5899EXdtyHQ4qrHZeWJvGrsxy7h0WzL3DQvBsgVL1\ntw4KxM9FzxubMqm2/WGa+r00y7CIjm121RSGRpshc7PY4taZ7saqNintLFUVOf9N5BfvIH/5vuX2\nW1KEXL0YETcaERbV4DgRFumIdLr9ESgrRX31MUffjsJ85N4dqB++BtHdUO55EmE8vyQv0b0PnDhK\npLOdAFd9qysMOOXHqCiHYwcBRwSZTEtB7t6CumIR6gt/Q33rH1CYj7juDpR/foQy7QqUe5+GPoOR\nX72Huuqn85ajzGLnud9SOZBTwYMjQ5nYpeXKpbgadNw3PISMUgtf7M6tWb4ltRSdgMGhHVthXFxG\nY40ORcbeA6S4h3JLZOsXYJNSIr/9CLltHXj5IjetRl52Q7Of4mvte+lCsFoRs64951ghBCJuFLLv\nYOTSBcjli5C7t4LdDmFRKPc9g3A+f5u36N4H+ev3iGNJxIWHsfpYMZtPlmKxq1TbpeNfm8MJP62b\n93mV7m6Qnv1Br0f9eJ5jfmf6b4LDEbfcjxgyppbpTRicUP7vcdSP5iG/+x9qdTXKDFOzRCipsvHs\nb6mcLK7mkdFhDL8A+RB9g92Y0d2HxYcKGRLuTt9gN7amldE7yBX3dtxwqzFoCkOjzdhyshgMoQzr\n2fqx+XLJd8g1vyAmX4bo0R/1zeeQuzYjhlxyfvstzEfGL0UMH4cIDmv0dsLojLjsBuTIiagL5kNx\nIcrdTyFcW+iJtEss6PTIpL0MGxXLr4eLeGV9/Yl0rgaFad1avjmUcHZBTL0CefQgIiAYAoLBPxgR\nEOT429W9Qf+B0BtQbv87cv4byB+/RLVYEJdd3yR/Q0GljWdXnySrzMqTY8IZeAGf9uf2D2BXRhlv\nbcnkkdFhpJdYmHEBvtPWRlMYGm2ClJLNFi+6KEUENzEi5XxR1/zqKJ8+fDziyltASvAPQq5bDuer\nMH79HlQ7YubVzdpeBASju+vx85Kh3v0anSG6K/LwPvpdeTNvTu+EKsGoV3DSCYw6gZNe4c6fjpGU\nV3lBFAZQEzHWHIROB3/5GxickL+aHd/zFXPPuV2VTWVPZjmf7sqhoNLGM+PC6RNUN3O7JTHqFe4b\nHsITK0/yj7VpAAzt4P4L0BSGRhuRm5LKEbdQbvBqWuG235GqHfbtRFZWgM0GditYT/0rFER0N+jU\ntU5UUdX6lchvPoB+QxBz73U8oQqBGD0ZuegLZFZ6k94MasmUn4NcvwIxapLjCbqdIbr1QS5bgKys\noJNP/Wau2AAXknIr613XHhCKDm68GwC5bCFy+DhEaGSdcXkVVranlbE9vYy92RVY7BIvo47nx0cS\nG9A6WdY9Aly5rIcvPxwooKufc5PLoLdHNIWh0SZs2X8S8Gd4r+aZo+SPXzp8BQ2tBzA6Q9eeiNi+\niNi+UFJM8bsvQUwPlNv/7nhiPYUYORH589fI9csRV/3l7McuL3XURaooQ5aXQUUZVJQjD+52KJ/p\nzbOvX2hEbB/Hk/nRg9BnUL1jYgNc2JxaRlGlDe922mNaKArMmYvcFo9csQhx8/2AI0x21bFi1q5I\n5XBuOQDB7gamdPVmSJg7PQNd0bdyhvV1ff1JLa5mVNTF0aK2fZ4RGhc9m/Mh0ppLWKfuTd5WFuQi\nVy1GDB6FmH096PWnPgbHvxYLHD2ATEpEJu1FLviU33Oq9Z26ot7zFMKpdtSR8PKBfkNPOb9vbND5\nLfNzUV+436EkzsTojJh9HcK3nTbG6XzKj3EoEdGQwvB3vHkk5VUyrB0XyBMenoiRk5DrllM69Rp+\nydGx5HAhpdV2egS5M7d/AHHh7oR7OrVpVViDTuGpsRFtdvyWRlMYGq1OYbmFgzo/TOJYsy5m+fPX\nIFXEFXMR/vXU+nF2hYEjEANHOMYXFSAP7YWcTLwvv45CW/2lG5QxU1B3bkLu3IQYOqbucVUV9dM3\nHS1h73ocvHzAzR1c3cHVrcGKse0FYTRCdDfkoX0Njunia0SvCJJy27fCAMgfOR3vtb+y+qMv+abz\nDOLC3Lmipy+je0aSl5d37h1oNBlNYWi0Olv3n0QK0axkPZl+ArlpDWLirPqVRT0Ib98aBaDz9oWG\nbiax/SAg2OH8rk9h/LYEkhIRN92DGDi8ybK3B0T33shfHX4M4VLXj2HQKcT4OpOU1379GABrk4t5\nc3M5DwT0ZXLmVgbddgsRwb5tLdZFj5a4p9HqbDpRTEhFLlF9Ypu8rbrwM3B2QUy/qsXlEoqCGD0Z\nDu9DZqXVWiczU5E/fA594xCjJrX4sVsL0b0PSBXOUp8pNsCFo/lVDRbRaw/8nFRIhJeRPjddj9Fa\nRdietW0t0p8CTWFotCql1Xb2VbswrCIFxS+wSdvKQ/tg7w7EtCsR7hfGiShGTHDUXVq3/I/j2myo\n/3sdjEaUm+7pkJ3SaugcC3pHPkZDxAa4YFUlx1u5DHpjyS6zcKyginHRnvh0j4XYvshVPyNt1rYW\n7aJHUxgarcrWkyXYhcJw38YleNCVAAAgAElEQVSX9gZH3oa68FPw8UdMmHlhhOOU87v/UOTm35BW\ni+PYv5rhxFGUG+52rO/A/OHHOIvCONXcp72G125JdQQc/J6lrUyZA0UFyK3r2lKsPwWt4sMwmUzB\nwItAP7PZHHfachPwT+B+s9m85LTlE4E5QA4gzWbz860hZ3th5dEiNqeW8ujosA5d2fJMpJSsOJBN\nQFUBMX2im7ZxwkZIPoy4+b46EU4tjXLJFNSETcidmyEwFPmLGTFsHGLQiAt63NZCdO+D/OV7ZGE+\nwqduXw0fFz3B7gYO5lYy+9w9mlqdzamlRPsY/0j47DXA0aBpxSLk8HFtK9xFTmvdjUYBPwE17/Im\nkykayAVSTx9oMplcgfeBB8xm83NAX5PJNKGV5GxTpJR8k5jL21uzSMgoJyGj9QvEXUjWnyjlUBmY\nUlahxPZu9HbSZkNd9AWERSFa44bwu/N7zS+on7wOXr6Ia2+78MdtJURfxzOb+uit2F97EnX1YmR+\nbq0xsf4uJOVWNKnJU2tQUGkjKbeyVg0oIQRiyuWQcRL2JbShdBc/raIwzGbzAqD0jGXJZrN5TT3D\nhwMnzGbz7wbUjcCMCyxim2NXJe9ty+bbvfmM7+yJl7OO9SfaZ3ey5lBtU/ksIYvoiizGGYsQno03\n7cj1yyEnE2XOTY5M3wtMjfP7WBJkpaHcfF/L1XRqB4jobijPvI6YcRWUFiO//Qj1sVuxv/gg6tIF\nSJuV2AAXCqvs5JS3L7/A1tRSJDA8snbIrxg8Gnz9UZcvahvB/iS0x7DaQGorl5JTy+rFZDLdDtwO\nYDab8fdvXtKUXq9v9rbnS7XNznPLDrHuWBE3Dg7njhFRvB5/nMX7snHx8MbNePafSVVVTp48SURE\nBDpd42+orTnn+ZuOk1el8reUpQQ89QL6M46rlhRj2b8TYXBymJyMzggnI0Kno2DJdxh6DcBn3NTz\ndjg3ds72WSbyl/2Ay4QZeFwy8byO2ZY0OF9/f+gfB7fejy0jleqt8VRvicf6w+e4eXoxbMQs3t+e\nTXqVnl6d2k8i4o51mUT6uDCgc2idc6F89nWUzf8v6rEk/Ls0PQKvI9Na13J7VBg5wOmPD56nltWL\n2Wz+EPjw1H9lcxN2/P39WyXZp6qqivz8/JqPVPSsqAwjKd/CbYMDmdndnfz8fOICDSy0qyxNPMHY\naK8G9yelJD4+nsTERAICApgwYQKBgY2LPmqtOeeVW/hi20mG5R2k99VXUuTiXicXQv38beT6FQ3u\nwz77evLz62992RSaMmfxr4+pdnalugMngTVqvk4uMHqq4/Pyw5St/BmPYRNw1itsT85hoH/78KOV\nVNvZmVbMnJ5+9Z4LcuAI+O5/lCz8HNtfHmwDCduO87mWQ0NDGz22PSqMzUCUyWQynjJLjQTebWOZ\nzouUlBR27dpFQUEB5eXlNcv1BgM2qxUnpzQenDKVS6L/MNN0D3DB31XP+pSSsyqMXbt2kZiYSExM\nDBkZGXz33XcMHDiQIUOGYGiB3g7nQlVVKisrsVqtWK1WbDZbzd/e3t74+fnx5S87sEtP5nY11tjP\nT0dKiTyw29GGdPb1jtIelmqwViMt1QgPb0cxwVamJfpQdDTEiPHIr95Hl55Md3/ndhUptS2tFFXS\nYA8L4eyKGDud6qULUCZfjghvYmCFxjlprSipMcCNQIjJZHoKmAdUAU8CUcDVJpPJajabl5vN5gqT\nyXQX8F+TyZQLJJrN5pZv6NtKpKens2TJEtzd3YmMjMTPzw9fX1/8/Px4c0cRuSlJdCk9SOmBTdgj\np9aYlBQhGB3lyc9JBZRU2+ttH3n48GE2bNhA165dmTp1KtXV1WzcuJGEhASOHj3K+PHjiYioW8dG\nWq3I9cupCotARsQgXJtX6llKyffff092dnaDYyJdvVjjMpTL7UcJmT6r/kG5WZCfg5gyp45i6MAZ\nDx0SETca+d3HyE2/0b3HZSzYn0+lVcXF0PZvGZtPlhLopqeL71mi5KJiQFFQ338V5a7HIDSyY+fN\ntDNaRWGYzeZ4IL6eVS+e+pw5fiWw8kLLdaEpKChgyZIleHl5cdVVV+Hs7Fyz7kBOBdszyrlxyEBi\nrAGsW7eO5cuXM3XqVBTFcXGO7uTJooMFbEktZXJM7TaS6enprFixgtDQUCZNmoQQAmdnZyZMmEC3\nbt347bffWLRoEb169WL06NE4OTlCEGVVBeq7/4SDeygG0Okgpieib5zj04TS3idOnCA7O5t+/foR\nGBiIwWBAr9fX/Ju1cztfJevx0Jfh5lZNeno6YWFhdS5geXAPAKJH32Z8yxotiXDzgH5DkNvWETvS\nhCrhSH4lfYMvbP+IhpAlRVBeSqV/KLuzKpjezbtBBSCtVuSC+Y7/ZKejPncv+Pojeg9G9B0MsX0d\nfUE0mk17NEldFFRUVPDzzz+jKAqXXnppLWUhpeSzXbn4uuiZ1d0Ho94PVVXZsGEDK1asYPLkySiK\nQmcfI6EeBtanlNRSGKcropkzZ6I/o+dDREQE1113Hdu2bWPnzp3k5+cze/ZsnKorUf/7AqQeR9x8\nH97de1G0bgUycQfy+0+Q338CgaEoV96MGDDsnHNMSEjA3d2dUaNG1XG2y9ISDu0+yKHIWcz2KaY4\no5AffviBkJAQRo4cWdtuenAPePtBUPP6UPxZkKrEapM4OV3Yp31l+ATUhE10y0kCvEjKbVhhyKoK\nMLpcsKd49d2XITWZ7XfMw6ZKRpylIKJc8wvkZuH1xKsUv/eqY2FkF+TWeOS6ZQ45r/krYuRE7a2j\nmWgK4wJgtVpZvHgxFRUVXHHFFXh51fZBbEsvIymvkv8bElyTmDdw4ECklGzcuBEhBJMmTUJRFEZ3\n8sS8N5+CShs+GUexfT+fVV4R6AzOzJ49u5YiOh2DwcDIkSMJCgpi2bJl/GA2M+vQFlwKs1HufhLR\nNw4nf38U/xBHb4G8bOTeHch1K1DffwXltocRg0c1OMesrCzS09PrVRYAlV++x+eBl9DJFeZOHYJU\nB7F//34SEhJYvHgxt956K3q9Hqmqp8ptD9Yu4rOgSslvG0uoyFBRPSQuIQr+gTr8XA34uujxMOpa\n7vvrNQA8vHDd9huREVc3WIhQFuShPn8vos9guPXBFv/95NGDjtBmYPP2g/h4d6Z7A82PZGkJcsl3\n0HsQznGjKMnJRn48D3H5jYg7HoEjB1B/MSM/ewu5LwHlxnsQbhdPqHRroSmMFkZVVZYtW0ZOTg4z\nZswgKKh2RVW7Kvlidy6hHk5M7FJbkQwaNAhVVdm8eTNWq5WgoCCCLCrhlYUsXZvLZWs/w7kgh5Fu\nmRge/ReenueupxQTE8OMYYP5dcMWfvSO4LJrb8O9V/8644R/EGLcDOTwcahvPo/60WsIKVHiRte7\n34SEBJyMRnbaQ/hmWQpOegUnReCkFzhZqiiy9yTX2Yf7hkegUwQoevr164efnx8//PADR44coUeP\nHpCWAmWl0KOuTBcDUkq2byjHxVWhz6CmO9GllGxPL2PB7nyGl3lRgg2XEgVdKRw4VM0BtZAjshI/\ndz3/ntqpXl9XUxF6PWLoWOSaX+je53o2ZVaiSolypinR/D9H46it8RARjZgy57yPfTrqyh/B1Q3L\n9KvZmR3COH1RHRlqZFn8NVRXolx1i2MOcaORK39C/vgFYtAIRI9+KN17I5f/iPzpS9Tjh1FufcBR\njFGj0bS9J+si4vcQ1+TkZMaMGUPnzp3rjFmTXExqsYUb+/s7bqRnEBcXx7Bhw0hOTmbz5s3sT9hK\nt4rDhG/+EeeCHJJ8QwkuL8J/R30uoXpkOryfyM/fZGbeMUpdPPghIZHS0oYTAoWzK8r9z0KXWORH\n81C31j1OYWEhx44doyJiCIsPFyOEQEpJqcVOZqmVI1klpLkGMinSpY4pIywsDB8fH/btc/RkuNj9\nF+knrGRn2MjOtDVpOyklOzPK+PvyE7wUn05olRG9EFw+zYdZl3vTuZ8TQZ4GRug8uckpkMgKZ349\nVNhicosR48FuI7YomXKLSlqJpbZ8B3YhEzYiLr0OMXgUcuFnyNOyrHekl5FW3PzihTInE3ZtQYyZ\nxu4e46nWOTFs+yJkUT3htBknkfHLEJdMrWnXKhQF5cqboSDPUZYeR3tXZdoVKI+9CgYn1HlPof7w\nGdJW97dRpeRgbgV2tXamu7TZUH/6qk5m/J8F3XPPPdfWMrQkz53tZng2XF1dqaioOK+DJyYmsm3b\nNgYOHEhcXN3w0Wqbyivr0wn3dOKWAQF8uSePeRsz2JNVQXaZFVVKvJz1REWEM2TIEOLi4hg8eDC5\n+DFi0yJsXXsR+Ng/0eXnINf+iujZ/6zd3dRNvyE//Df4+OH9wHOEd+vOvn37OHz4MJ07d8bX17fe\nOQu9ATFoJPLoAVi1GAJDEOGdatZv2rSJQyWCrWoEl0R58sy4cCZ28WZyjDdTQxSmz/87syOdGHrp\n5Lr7FgK73c6BAweIiYnB+befQdGhXIBy5fXREr9zY7FaHG8XdhvYrJLO3YzodGc329hVxxvFW1uy\nWHigAL0CN/cJxCfXQGikgU4xzhj0CoH+Brp0dSYwRI/dAq6lOvbklzOiu0etNqTNna/w8kHu3oIx\nP5tfvXrT2ceZLr4O86e0WlHffhFc3VBuewjRb4jDD7ZhJWLgCMoMrjy87ATHC6qY2MX7HEeqH/nT\n13DyOMptD7HgaCX55Rb+mrQQkZmKiBtdy/ylfvIGlBSj/N/jCKNzzZyFfxAy5QhsXYcYPbmmBpnw\n9kOMnAAlRcjfliD3JSAiomvqakkp+SQhh3e3ZVNSbWdw2B+mK7k1Hvndx1Be1ig/X2txPue1h4cH\nQKPq9WlvGC2ElJKdO3cSFhbGyJEj6x3z6+FC8its3NQ/gAUHCliwP59ILyMFFTa+Tszj6dWpXGs+\nzENLU/hyTx4WVWAwGJi4dwkG1cbG4dfiZDQirrsTfPxRP56HrKx7kkirFfWr95Dz34DO3VEe+RfC\nL4CQkBDmzJmD1WplwYIFFBQUNDgf4eyCct+z0K0X8n+vo25ZC0B5eTkJh1I44NGXTj5G7hkWXOvi\nlWuXgtWCmDS7wX336NEDnU7H3sQ9cHj/Rft2cWhfJdVVku69HTfakmJ7g2MzSix8tiuHWxcd5eX4\ndHIrrNwZF8S7s7oQbjFit0O3nnX9VT5+egYOd8XoKeiturLycHGLyS9GjCfkWAIeBjh0mh9DrvoJ\nstNRrr3DkZlvdEa5+wnQKajvvMTGY/nYVMmB3EpSCquafFxZXorcuAox5BJsHr5sTy9jSIQnhkuv\nhT3bkDs2/DF2307Yl4CYYUJ41M1XUq68GaoqHf6N0+fm7IIy916UOx+DglzUlx9Gff9fyJwMzPvy\nWXyokEgvJ5YeKWLZEcebm5QSueJHx9/b1iELzz+RtKOhKYwWIjc3l9LSUmJjY+t1/pVZ7CzYn8/A\nEDfSSyx8tSePsZ08eWFCBP+dGc1XV3bl6bHhzOnph1EvWLg/nweXpnBszwGcd8Szodt4lpY4bODC\n1Q3lrw9BQS7y6/drHUcW5KH++3Hk2qWIKXNQHngB4fGHryMwMJA5c+ZgsVhYsaLhzGrAcSO492mH\n0vjkDeTOzWzbuZvdbv3Q63U8fkntarrSanFEqvQZjAipv4/xO1szeXFDDjExMSQdTMJqtSIuQv9F\ncaGd5KMWoro4ERHtCGkuLaqtMKptKr8dL+aJlSe4a/FxfjxYQIyfC0+MCePD2V2Y1s0H1SZJOVpN\nWKQBd8/6/RNCCOKGuOEsFI4cqKpjRmkuYsgYhE5HrL2gJoFP5uc6br79h9XqCy78g1DueBSy04nf\ndoggdwNOOsGvh4uafFy5dilYqhGTZ7M3u5xyq8rwCA/ExEshKgb5zYcOJ7fdjvr9JxAQjBhff8l7\nERqJGDURuXapw8x15vpBI1Be/gAx8xrkvgSWvPclXyfmMS7cmTemRzMwxI0Pt2ezP6cCkhIhLRkx\n3QSqilz9c5Pn1tHRTFKnOF9TRWJiIpkZGYzdswbdgV1w4hgyPwcqy0FR+O5wOXuyK5nYxYv5O3OJ\nC3PnoVGhNX4MJ71CqKcT/YLdmNDFm15BLqw/UcKSdDsuTnrklDmsPlHB6CgPPJ31CN8AkJKTW7Yx\n3xrBW4mlRJZlEPzeM1BUiHLbwygTZyGUus8Erq6u2O12du/eTXR0NG5uDcfYC70eMWgUctdmKpOP\nMM/WjSKDN0+OjSDGr3bEity0GravR7nhLkRAcN3vKKucjxNyyCm3MbF7ICePJuFlqSLwyhsQBqdm\nf/dNoTVMUlJKdmwqR7VD3Eg3jM6C5MMWnJwFQaGO7PutqaW8sDaNNckl6BXB5T39+NuIUKZ09Sbc\n01jj3D1yoIr8HDuDRrhhNDb8fOfiqnAy14JbqY5svYXoAOfznq8wOiNTjpJbUMoGpwhmdPfB8OXb\nkJOBcu/TdRI+hX8QOU5ezK8O4zJS8YsMZ/2JEqZ388FJ17hnU2m1Ij+eh+wSy54+k5m/MweLXXLX\n0CD0Oh2ic3fk6sVQmAdlJbBpNcrce2qZTOvMOSrG8SBTmIcYXPftX+gNiNg+rIsaybuWTgzJ28/f\n1r+FTrUxePQgNqeXs+Z4CSMSf8GtotjxNpWdjtyxATF2OqIVKiqciw5hkjKZTNPOZ/uLiWPHjhFa\nXYZLUQGknXBEaHz+Nuq8p8h7+gEW78+ld6ALXyfm0TPQhb+PCq1laz6TPkFuvO51jP75h/gkbAJb\nchyOuQ2nKtgezqvkFc9R3D/kYTYX6XC1VvJakkqybzTKk/PO2bthwIABuLi4sGXLlnPOTRiNiJET\n+Mi5F1mGQK7o6kr/kNo3CyklcuVPEB4NsXVNTFa7yvvbswl0M+CsV9ha5IyPamV/SOeLqhIsQFqK\nlcI8Oz36OuNkVBBC4OGtUFJkJ7fcysvxaby8Lh03g47nx0fw3qzOXNnLD1+X2kGLlmqV5CPVhEYY\n8Gjg7eJ0Rg1zRwpI2V/dYmXJleHj6Z59EICkhL2wcxNiugnRQLfEdWEO393odZ8zLWsrVTbJb8cb\nbyaT29axH2+ejr6a59ekUWWTPDAypEbhiPBOiGlXOXwJC+ZDt14w4Oz91YW3L2Ly5cgdG5DpJ+sd\nsz2tjDf3lNAnyJWHrxyCrldf5M9f4/ruCzwxxBerzc6/DAOwjJvpMMNNuRwqKxyVlP9ENBhWazKZ\nbmrE9o8BS1tOnI5JQUEBBQUFjM5PR0ydgzLxUqRqh4I8KrOyeGt3OXbpsANHeRt5ckz4ORsjybIS\nPBZ/wePhnVg6aCyf7spFrwiWHilkX04Fe7MrcHNSMHU2Mv2bl7HaVR4d9hAv97yRf3sFUbctTm2M\nRiMjR45k1apVZGZmEhISctbxOyLiWJNbRrQtmxviLqk7YN9OyExF/OWBek1yPx4sIL3EwtNjw9mW\nVsaa5GIezEtje2A0ubm5BAQEnEPijoHVonJgTyU+froaUxSAh5eOlOPV3LMkGVVKbuofwOwevmd9\naDh+uBq7DbrW47uoDxcXHc7hAv80JzYfKGNEr4aT3BpN3zhivngfd2lheWI6gwJDEZMvr3eolJL4\n5BJ6+jsT2LULgb9+QteBd7N0SxHTT2ShxI10vBk3wOG8Cr7ab2f3gLvwUXXcEefPpC7eGM4IFBDT\nr0Lu3ASZqSimWxuV/yHGz0QuW4BcvxxxTe3eJvuzK3h1QzqdfZx5YkwYRoMO7nocdWs88tM3CX3n\nSf4WNZR/usfxjkdXHpIS0akrdO+DXLUYOX4WQv/nyFA4213rTeCWc3zq2h3+hBw7dgyA6JIcRLde\ngCOEL9/VlydOepIofNFLFX+qeXZ8BG5OOoevYfVi1K/fdzSwObAbWZRf82QoF30JleXorr2DWbG+\n/HtKFO5OCkVVdo4VVHHzgAA+vqwL1/X2w1Otws9SwpOuxyi3qrwUn0aVTT2n3EOHDm3UW0ZJlY3/\nJJbhbi/jrrTl9V6g6sofwdsXEVc32S+7zIJ5Xz7DI9wZHObO1K7eWOySLEMQOkXUhNheDCTtrcJi\nkfQZ9Ef28/GCKpalFiJUwQA/V96eGc0VvfzOqiwsFpXkw9WEhBvw9G58bsX4IR6UYiftoAXV3rS3\nDLvqeBs4ml9Vcx4KgwHnuBFcmvwbOzy6cHz2nQ2aYI4XVpNWYmFsZ2909z2D8vKHTAvRkW7wJnHV\nOkfDplceQV23HGmpHXL76c4c/r78JMec/JjrU8wHl3ZhejefOsrid5mU+55Fue8ZRFRMo+YmPDwR\nA0c4Wu+eduyMEgsvxqcR6Gbg2XHhuBr++K6VoWNQHngBigsYvHUh11UfZH16JYsOOIJFlMmXQWEe\ncsf6RslwMXA2tfi12Wy++2wbm0ymd1pYng7J8ePHCdKBh14Hp2ypxwuq+MfaNCqtKt39ncnIruTZ\nlIV4xh/HvnMTHD/k2NjoDNVV1FzaLm4QHAYpRxATLkWEOeLKO/s68/bMzrywJpUj+VUEezjhatCh\nfjUfbFYYMJzo5V/w8M3P83KKZN7GDB4bHVZvrsfvGI1GBg0axIYNG0hLSyM8PLzecR9vz6TKJpli\nSaJLyj5k+glEWFTNepmaDAf3IObchNDXvplIKflwezaKgFsHBdXMJYZSVocMZ1ZEBUlJSYwcObKm\n3tWFwGqVnDhajevApuVDNIWiAhspxyx06uKEl4/j0jqQU8Hza1IJ1TnRAzfmxgYS5H7ueSYfrsZm\ng269mlb7yGjQ4RIF+hM6tu8pZ8bk+p/opSoRZ5wba5KLeWtLFgDB7gZGRnowKsqTTsPHM339k/zc\naTzflvvxdAPHjk8uRq/AiFPNjURAMKNnBfLpomMsm/R/9LPuRG5fj/ziHeSiLxz2/3HTOWwxsuhg\nAeMqj3Pr4UW4X/8u4hxv4MIvAPya9lYqLpniiG7asQExwtHE85u9eahS8tz4CDyd694ORbfeMGQM\nxC9lTsLXnJj2LJ/vzqVHgAuxvQdBSIQjGXDo2AteqUBVJQLq/G6tSYMKoz5lYTKZgoAgYC+gnEuh\n/BkoLS0lOzubYWU5jiJ+io6E9DJe3ZCBm5PCSxMjeHJFCqMKkwg8nog8ngiRnRGX3eDwMwSFQUkR\nZJxEZqVBRioyMxVieiBmXVPrWB5GHf+YGMnTq04yb0MGz3Wz0WPjasS0KxAzrkH958MM/P41/nLT\nK3x8oIxPd+XU3KQbom/fvuzatYstW7ZwxRVX1Dnpd6UWEn+ynE6WVGaPG4LYvhC5bT3i8tMUxsof\nwcmIuGRKnf1vTStjR0Y5twwMIMDtD2UyKWcH7wWOwzPSCeuRIxw+fJjevRvftrUp2O2SHRvLycu2\ncfJ4GoNHujTpqf10sjOs7NtZSWWlihCc9hHY7RInJ0FsH8dN/mBOBc+vScPP1cATY8PZ8ms5JUUq\nIfXr5RqsFpXjh6sJDmva28XvTB7oxZcn8rEflVSO+kNBVpTZyUyzkplmpajQzoix7vgGOG4BVrvK\nt4l5dPF1ZlpXbzaeLGXRwQIWHiggxN3AyNmPM93fF/PhMg7nVdLNv3bAg12VrEspYVCoOx6nZZs7\n6RQmdvHix4MF5M++HP/pV8Hh/agrf0Qu+Rbbsh/4YOQj+Bjc+euO+bjOuurCOZG79YbgMOS65TBi\nAmnF1axPKeHynr61zs3TkdXVkLABeg1EVJTxf7+8wK5LnmfFsSJ6BIYiplyO/PS/cHA39BzQYqJa\nqlVKiu2UFKmUFNkpKbJTWmLH3UPHqInu58znuVA0yvBmMplCgM+BCUAyMAiIN5lMfzWbzdsvoHzt\nnt/NUV3SjyJmXcXyI0W8vz2LKG8jT48JI2P1airVaAZUpDk2uGIuuqlX1N6Jlw94+SB69Dvn8Zz1\nCk+Pi+Dx5Sm8tL+KF8N60nnGNQijEeWOR1FfepDpK98ma9zf+DmpkFAPJ6Z1a7gdql6vZ/DgwcTH\nx5OamkpkZGTNurKKSl5fl4KzCveO70Fop0jssX2Q29chL7vekeFdlO9QIJdMcVQ6PY0qm8pHO7KJ\n8jIys7tvzXJZUsSoQ6v5NPASthYZ8ff1Zd++fRdEYUgp2b2tgrxsG916GUlLsbFxdSmDRrgRGNL4\nG1NVpcr+XZVkpFrx8FTo0t2IlCDVUw5/CVJCRCcnDE4KB3MqeG5NGr4uel6cGImvix43d+WsuRi/\nk3LUwv+z997hcZ1l3v/nnDnTi0bSqPdmWc2y5d67E8dpEDKQQIAsbSlLgOXNLi0baiiB7EvbXVgW\nAoEkk+YkTtx7kbtly2qWZPVeR9L0mXN+f4wsW1axbMfAu9fve1264pz6nDPPee7nue/v/b2DAZhV\nMI2M9zQwaiQM6QJCA+zf14XVotDREmBolNZrsapQqwWqyj0sW2tCEAR21A7S4w7yhSUJzE0wsjHb\nypA3yPHWEY42DfF6l4G1VhVmrYqXynt5au142nR5l5sBb4g1GRPlau7OsfJGZT87awf5yNwYyC1E\nlVuI0tnK7j2nqRcsPHHhRfQqENbcOR6NIAgIK+8KC222NeFoDFN/H8yLmvIcpXQvjAyHE0vTstH9\n909Z1H6W48znc4vikRatRnnjBeSdW1HdpMFoqPXR2xUkGFQIBpTr/nv1OI1WwGJVkZyqobnBT025\nl/y5k2tq3WnMlCX1n8DrQDTQ7HA4BoGNwDN3qmH/r6C+vp4ogw5tKMhvpQJ+fbKTeQlGfrAuicjX\n/5tzFy8jKjJzvvgFiLJBfc1t39OiVfGUWIEu6OG7eR+lOxCebQgJyQiPfR5qK/l4804WJhn5zeku\nznW4pr1eQUEBJpOJ0tLSMd+1z+fjJ1uP4UTPRwoiyE4flVxYtCpcv6KxDgBl3zsghxA2TKx18XJ5\nL73uIJ9dFDfOX69UX0Af8rM6TsXRlhFm5RXQ3d1Nd/eUhRVvCYqiUFHmpb05QN4cHbmFeu79QAoG\nk8jJwy4a624sXaEoCjct9xkAACAASURBVM2XfRzYPkxnW4DcQh2rNpnJm6Mnv1hPwTw9hSUGiuYb\nmLPAQKRNoqrnqrH4/sbUMfaTxaqakIsxGTpaA0RGq8bcWreCLXOiqMJNV5OHmnIvKhXkF+tYt8XM\n6rvMzCrQ0d8TorcriDsQwnGxjzlx49lvFp3Epmwr316fyl3ZVg42OtmYGcGZdte4RD6AAw1OjGpx\nXFb0FcSZNCxIMrKrfpDANXEVV2QCf9YVkBelYfXyIoSPfmHCpKO8vJyjR4++Z6wvYek6kCRaDxwc\no/xGTOKKAsLCmLvfgvQcyMkPT8o++y8skwZwKyLnmgcQ1GqE9fdC5bmwa3aGCAYUKss8DPYHCQUV\n1BoBs0VFTJyalHQNeXN0LF5lZOP9FjY9YGHpGhPFiwykZWmor/HR133nXKvTYaYGw+xwOP7D4XAM\nQNjd7nA4um/i/P+VcLvdtLe3o1Mknlj0Vd7tgvtmR/KNxVFo/+sZlEM7KEtfTG6MAbNRj1C8KNyx\n/LeusQOg9HZh2/5HnvKdIiBKPL2vhUFvuAOJi1cjrLoLccdrfMXaRWqElp8caaPtOi2gayFJEosW\nLaKrq4vGxkZ8Ph9/2fouF+R4CiJF7iu5qoklzFsKKim8yvD7wsv74sUIsePLPDYN+nizqp8NWRHk\nxV4nuld9AfRG7pqXij+k0K6JR6VSvefB78s1Phou+cjI0ZA1OzxbN5oklq8zExMvUX7GQ0WZZ9LB\nSFEUhp0hSg+4OH/Kg9kqjg204jTugOoeD9/ed2VlkTKOKmuxqnCNyAQDUw9+fp+McyBETPztuWWi\n9BLmVJFDipOiNTpWbDCTNVuH0RR2F6VmatAbBKrLvbxVNcCQLxSe/U+BhwqiAQHnaDGvFy9cLQfq\nDcqUtoywLNU8Zb7FPbMicXpDlLZczZP6y4UeRvwhPrMkEdU9H0BcvHrcORcuXGD//v2cOXOGioqK\n23gbVxEOfi/nlV4talHgwfypVxdcOAnd7QibHhxz1QqiirlbNmEMuDl6MqykK6y6G7Q6lF1vTLiE\n4nahNNWjXLtkAHq6AsgyzFtsYMUGM0tWm1iw3MjcxQYKSwxk5+mITVCj04vj3MT5xXoMJpFzJ90E\npulHdwozHfB1drt9HB3BbrenAn+dbKu/U1ysqUNRFN7QFKJXwQ83pfKJLAme/TpUnmPo0S9wWTEx\nLzE86xKKF4dLj1ZfuK37yi/9FgSRdPuH+OaaZHrdQb6zvxXfKDNK+OAnITkD7fPP8bViPSpB4PsH\nW3H5p57d5uXlYbFYKC0t5e233+aYOxqVSsUTq9LHHScYTVBYgnLqSFil1DWMuH58lm1IVvjViU4M\napGPTTIIKVXnIbeQzGgDs6J17G70kJOTw6VLl5DlG7O7ZoLWRj+V570kpqgpmDe+XoOkFli4wkh6\ntobLNT5OHXFRV+2l/IybE4dG2L99iHdfc3JgxzDOgSBzFuhZttY0Zab1FVT3eHh6XwuRehXf25BC\ntGH8oH8lHjE8NPXv0Ds6c4yJv32a5sNzbHRrAjxzvG1sQnEFKpVATr6Owf4Qp6pGWJJiItc2tZsj\nxqhmY1ZEeJWRHcG5DtdY9vfJ1hG8QXnaUsJzE4zEm9S8eykss9E44GV77SB3ZVvJiJwY2K+qquLA\ngQNkZGSQkpLCoUOHppWyuRm0L7qLw9FF3G0cwjrF6gJA3rUVomMRSsbnNGlyZrOYXk56jfj7ehGM\nJoSVm1BOHQ4zH1/6LaHnniL0fx5HfuIR5O99Gfm5p8aJHHa1B5HUjMWQZgpJLTBvsQGPW6by3F+/\nfO5MDca3gbN2u30vkGe3298GTgNP36mG/T1DVhR21A6w/WQFXlHHfS3H+GlUE7P9Pcg/+D/Q3Yn4\nhW9xIX0xCjDvyjJ/ViHo9CjnT97yvZWy43D+JMJ9jyBEx5AXY+CryxOp7/eOfYyCRov4mSchECTm\nhZ/xZEwvnUM+nt16lsBrzyO/8Gvk3/yEgR88Sehn3yL0wyfh+1/hg5WH2XxkK32NXXRrYvnQnJhJ\nGT3CwpUw2Iey4zVITIXrJKIdF3up6fXw6YXxE5gnSk8n9HYhzA7Ha+7KsdI65Edljcfv98+4kL3X\nI1Nd7qGh1kdXe9g/f2Xm3t0RoOykG1usxNzFhknZK6IoUFgSdil1tQepOu+lrTmAz6tgsqhIz9JS\nWKJn7WYLaVnaGzJgavs8fHv/FWOROsFYAFgiwp/b0DRuqZ7O8EBijbp9mfJYk5of3ZdPvyfI9w5c\nnVBcQUqGhpBaoUgx8uicqUUsryC8ygCnN0SEVsWLF8KKrQcbnNgMEvmxUxscURDYPMtKVY+Hy/0e\n/utUF0aNig8XT5xQ1NfXs2fPHlJSUti8eTMbN25EkiR27txJcBJl2ZvFKyNRSEqIByqnlvaQj+6F\n2kqE9fchTFLvZcXiPNySjnPvhAuDChvuBwSUl36LcnhXWJwwbw7C+z+G8MCjcKkC5fXngTBDras9\nQGyCGvEWGE9RNons2VqaG/x0tgVufMJ7iBmZN4fDsdNutxcDjwA1QAvwTw6Ho/EOtu3vEr6gzDOH\n2rjQ5mS1v4+cuDjuOr8N4f6nwtXsZBnxyWcQUjM5d6wds0YcU/kU1GqEghKU86dQPixPKtsxHRSf\nF/nF30JSGsL6qzGDxSlmiuMNbK3q555ZkWglESE+CeFjX0D5zU/Ir3+GTyUs5j9zH+KFyz4+2l0K\negOy0QSiCjRaMFnQxCXhulTNqaj5pFjUPDB78uW6MHcxiqSG7g6ED3923GBa2e3GcbGPdZkWVqVP\nDICOyZnnhw3GijQLvzvTzfkRPRLQ0dFBbOzkWcTXorrcS0vDRDebWiMQCiqYI0QWrDBOyyYRBIHM\nWVqS0sIfrlp9a8yThgEvT+9rGWOxTWYsAPRGEUma3mD0dgWJjpVuaSCZDIUJFv55eSI/PNTGs9dR\nrfu9QY75hlgpRqAeFuEGwrLhVYaV3fWDvC8vmlcq+jjeMszZDhcP5kVNWaviCtZnWvnz+V7+52wP\nlT3hAmLm6+p3NDU1sX37duLi4tiyZQuSJGEymdiwYQPbtm3j+PHjrFgxdWGvG6F9yM+hpiHuNQ5j\nrTuP0tqAkJwx7hj56B6U538BecVTBuGLc5Mxnb3I0V6FRaPXEL/zy/D3FBUz4duWh4dQdr+JnJHL\nYMYS/D6F+MRbdzvmFujo7ghw/pSbyOj3IEFzhpgpS+pnDofjK8AP7nB7/q7hC8p872Ar5Z1uHk31\n0zkgMycwCJKEcnw/DPYh/suPEFIzw+ycDhfFCcbxuRBzF8GZo9BUDxk5N3V/5dU/QH8P4r/8cEJm\nqb3Qxjf2NLOn3smW3DArSly4EiU9B4IB7tYbaa72sJVVpNs/yNrMCKJttnEz+pCs8Pa+Snq6VHxX\nVY9alTVpOwStDixW6O+Ba6ryjfhD/OxoO7FGNZ9acJXOqww7UcpOoJw7HqYfRsVAfJhbqpNE1mRY\n2F07yN1GIx0dHRQXT88W87hlWpv8pGdrmFWgw+2S8bhk3KN/igy5RboZG4DpNJpuhGanj6f2tqCT\nRL67PgXbFMYCwgbKHKGakinlGgnhdslk5t4aO2oqLEkx86kFcfzmdBe/Pd3FZxbGIQgCL13o5TIe\nNhqt1Fz0kpCkviHH/6GCaHbXDzLgDRKhU/Gzo+3ICtO6o67ArFWxItXMvoYh0q0TC4i1t7fzzjvv\nEBUVxf333z8uLyczM5OioiLOnj1LamrqODbfzcBxsTes3bUqD3arUQ7tDKs/j0I+shvlj7+EvOJw\nZcopNM4kUWBJWgRHQwV4X/0j+i/924Q43rUQHn4cpakO5fmf0/VIDoKgJSbh1t2Ookpg3mIjh3cP\nc+G0h8Skv048Y6Ytfmw0ZrETeNnhcAzdwTb9XeJaY/HE0gS8NccYMhiIa6oGWxycOhwuJpOZC4SD\nvgPe0FV31CiEogUooohy/gTCTRgMpfxMuAbGxgcQsvMn7C+I1ZMfo+e1yj42ZV+VU7hWBPATixRa\nRlr41YlOEi0abDYY8YU42+HiTPsIZ9tdDPlUrPXUU3DmJZT1q8LG4fq2DPbDaCEbobE2HNNQFH59\nopN+T5AfbkpD7xpEPn0kbCRqq8L80+hYhDVbwhTca2ajd2Vbw6qmJhvt7e03fBf1NT5QIGu2Dq1O\nRKsTibyRFsodQPuQn6f2NKMSBb67PnVGCXkWq4q2Zj+Kokxwc/V0jsYv4t57mYktuZH0uAK8UdVP\nrFHN4hQzey87uWdWJAWxes6UumlrCZCcNv0zXLvKeH9+NI6LfWREakmzTm3k/CGZ9iE/rUN++j3h\nZ8y1GcZNpLq7u3l321aSbRq2bCzBELiE6B1CDA4T0sTgtSxgxYoVtLa2snv3bh599FH0+pujlnYM\n+znYOMS9uZFE2SKR5y9DOX4A5aGPI2h1yId3ofzpV5A3F/HzXx+rnzEVVmRFs6fJTVmnhyUXzyIU\nlkx5rCCpEf/xX5C/+2U66waISkq47drsFquK2UU6Ks97qa8Zxnpjr+JtY6Y98wfAz4G7gV/Y7XYF\neAXY7nA43pso5d8Z/H4/z79zkJ6QlojoOMoGRbrdIebEGTjfMcJAq4tVaamIJ98GlQSZuQjXFAE6\nO0plnWAwjGbIzg/HMR78yIzaogwPIT//87Ar6n2PTXqMIAg8XBjNt/e3sr/Byabsif4FSRR4cmUS\n/2dHI88cbCW1fIDyjiFkJTz7K0kwsiDJxBK/AiecKPveQdj80ITrKId2gCyDVo9y6jBCYQn7Ljs5\n2jzMR2abyN77F+QD74Yz0JPSELY8HGZXpWRMGgtIj9SxJMJM0Dkb/8hOqlp7mZ0UPemxPp9Mc72P\npDQ1BuPfjqTXNeLnm3ubCSnw/Q0pJFpmxv+wWFU01YPHrWAwXmcwuoLoDAJG8515ro/Oi6HXHeD5\nsh72NTjRqMJ9JkKrwlIpculimCRwrTtMDim0twZob/ZjjlCRkq65usrwBMmK0nLPdXk+noDMO5cG\nqOp20zrkp2skMKZkIACxRomTrcN8akEsapVIU1MTYsMLfH3dSPigvvqxa4VzmyGoiQNdCnfffTcv\nv/wye/fuZcuWLTeVXX1ldfH+/PDsQlh1V1jE8PSRMIX2j7+EwhLEz319RurJRXEGzBqRoymLWfTq\n7xHzixHEqWNPgjUa78e/xkhlPCnNh1GUm2v/ZMicpaWzPcDJo72s22JGku5sQt9MYxjPjf7zHeAd\nu92+AfjD6Pn/6/SkAoEAP3vjMKWB5HAab7sCShCVoHC538MlWSGgm80HpJ5wtpYgIH7iK+OCY+c6\nXKRFaCf1ZwvFi8LJQz2dk8qAXwtFUZD/9MswG+lLT0/bkeclGMmO0vFaRR/rMyMmlQWxaFV8Y3Uy\n39jTjCcQ4qH8aBYkmciJ1l1zvIVQ4XyUna+jrNmMoL9Ki1WCgTCVtnA+gsWKcq6U9gc+yW9OdVEo\nDvHA7/8Nxe9DWLo2nIEef4O05lEsVJvwSEb6DHk8t6scITqVJSnmMfbOFf94wyUfoRBk592cZMZ7\niR5XgG/uaQmvOjekkhoxcxeSJWKUKeUMjTN4iqzQ1xUkPll9xyQmREHgiaUJDHiCXOz2YC+MHmMJ\n5RbpOXXERWujn9RMLR63TFO9j+bLfnxeBQQfXe0a6qp8REareCAmmu0N/fz8/syxLOmQrLC7fpAX\nL/Qy6A2RZtWSFaVjTYaFJIuWlAgNiWYNFaMZ8IebholxNXP08D6+tt6FW5NB0LqAkGRGVlmQJTMI\nIpGNz2Hu2cpA8ueIiYlh2bJlHDlyhIsXL1JUNLOa3B3Dfg40DLElN5LIK1TnnIKwtMfrfwyrLRTO\nD1ftm6HUviQKLE01cyiQi+/Cn9Ad24ewYuO4YwIhhd+c7iTGoOaBvCi6tJmAh9iyrSg7fJNOyG4G\ngigwb5EBgyECxJHbutZMMNMYxu+AbwGPAR8FYgEH8Pyda9rfBsFgkB9vPcbJYBKZlhGsxgANzTJr\nTP24upsJhUJ41WaOmZdwtM5JPqA89DhdARtdp9yoVJCco6Gy28O9uZNnWI8ZjAunxgWvJ4NybG+4\ntvEHHp8QnJtwXUHAXhjNDw61cbhpaEq/cqpVy58+kIPtuhjGtRAfeBT5+/+MsvcthHuvSpQoZ0vB\nOYD4sS0gqvCXHuCn28qRFC1fPPULpKL5YdfcjfQvroHPK+NxKogqiDTNY5W2gnqzhm01/Wyt6ifa\nIPFgXhTr0iJorPUTnzQzue87AW9Q5ul9LYz4Q3xnfcqklNDpYB6l1g4NhsZqYwAMDoQIBJT3hE57\nBSp/D8KlVzHJeoLqGEKaWARNDF9bncz+y042XrMKjUuUiIhUcanCS3dHkM62AIoCepOHnqHjuLyt\niIKO5PgSfL4sIkfUfFCIZd/+IbastlLpdPP8uR5ah/zkx+j5+urYKWm68xKMpFg0vHi6mcLO/awt\nsqBWdTJiW0/AMD5udv6Um6HeT3Bf5q/QO4/jsS5n3rx5NDU1cfToUQoKChBnQB75y4XxqwsYzfxe\ntQnl5d9B0QLEz/7rTddlWZ5qYVedk3N561iy9c8oC1eOuXEVReGXJzo40BD24O+oHeQhvQ2jWcRU\nmIvyxp9Q0jIRblNSxGBSYbPp6O39OzEYhNlRHwJ2Ad8Etjkcjr8un+uvgFAoxDNbj3PaH0eqpYmF\n6S8iCArzkx9gy6z34ff7qa2tpaamBl/IyS4lh5XxC2jsX4Z8xIWkhlAIjtQNE5QV5lyfsDYKIS4x\nPLM5fxKmMRhKTyfKi7+F3KJpS55ei4XJJtKtWl652MfKNMu04oPTQUjPgbmLUXa9ibL23nD+BaDs\n2wYx8VBQAorCy7PupU5l5cnhY8Q++W2E1MzpLzwJutoDoMCCZUZOHB7E5EvlqTXJuIMyZ9pd7Kwd\n4HdnurlwwU2xYiI5529XsOaP57ppHfLznfUp5ETfvDyDWi1gMIoTmFJX4he22Js3GIODg7S3t5OX\nl3d1daLIWLpeAX8HekBQrtJRo1VGHjPZoEsFXO0fCxLj2VuxgpDfQ3qqj4bOi1TW15Camop9w+PU\n19dz7Ngx4CQLStZQ2xeDbkjkrZ0DvOzrJdGs4WurklicbJp2lRQMBkkPtHI4EEtU7gKW5zUjuw0E\n9OnjjutqD9B82Q9oONT6MGtVr+AzFSJLEeTn59PS0kJvb+8NWXWX+70cahziofyoCTVHhDX3QEQ0\nwtzFt6RhVRRnwKJVUTp7PUsqdqFsexnhoY8B8HJ5Hwcahnhkjo2iOAN/PNNN0KlQqXVj2/xJCtqb\nkf/jh4hf/QFC2uQEk783zLR31gJrHQ7HLWfO2O32eOB7QLHD4Vg4uk0HPAu0ATnADx0Ox6XRfR8B\n5gEhoN7hcPzXrd57JggGg3xn6wnKfDbSrBeZn7yTqu6NzE/qwBV8gyMtjcyP/RQWQw4J5gTm7/oB\n5XM+xh9y7XwsS0tcoproGAmPW+bf94+gCkDX6SDNfh8p6ZoJ7BOheBHK7q0o7pFJCwgpcgj5f54D\nUUR8/EszpuCKo7GMnxxp53jLMMvTJlJbZwrxgUeRv/0Eyq6tCO/7CEpTPdRXI9g/gSCK9LgCvJW4\nnLU2geUf/odbvk9newCdQSA2QcIS3cNwXyKXqtzkFhhZlR6m51Z0uKg54qMt5OPFg93cMyuS+2dH\nTqoweqdwodPFO5cGuS83kuL4qasU3ghm60RNqZ6uABarCq3u5uIXTU1N7NixA5/Ph9FoJC0tLAqp\nd5ai9rUgZ32CXjIRg4NI/m5U/h6kQDeqQH+YiHBVJ5kkawv3znmLKFUtajGIO0JgaHYy+oQkAroQ\nxcXFZGRksG/fPkpP7MYWF8/ZUDGLhTg+lRnH3Yut00q2A4yMjLBt2zaknj4MMeto0iajde/GZywE\n4eqqMRhQuHDajdkikpiqoeZiMtWGOWQZtzGU8OGx+i0zoWH/qawHk0bk/QUTmRGCpJ5Ukn+mUIkC\nS1PMHGx04l9xF5qdb6AUL+KAmMiL5b2sy7TwwcJwPO6fChI4V+qhSfbyrUODLFr+ZT5++FfE//u/\nhZmPM3Tf/i0x0965wOFw9Nvt9sV2u/0eu90u2e32m+WlrADe5NopDXyJsDbVM8BzwO8A7HZ7MvBV\n4KsOh+NJ4JN2u/3mOKg3gVAoxOf/8DZl3iiyos+RZq1GIzzJ11Z9iPtnfYUc4yO0D11gW9U3OVte\nQerJ50lx1rK54xSXBFCnCsTEqxFVAkazijbBT360AbNRxflTHg7tGqavZ3zCkVC8CEKhcBH76zDs\nDHFx60VcbX0Ij34mLOV8E1iaYibJosFxse+2NHiE5AyEBStQ9r4drqG8/52wKu3ysDT0axV9IMCj\ny25+VXEFwaBCT2eQ+MSw7z4924jL20xthX9cRrTRJaGWRZYuMDEn3sirFX18blsDQ96/jqaOOxDi\n56UdJJrVPDaNhMZMYIlQMTIsExrVVQoGFAb6QjfljlIUhbNnz/LWW29hNpsxGo2cPRvuS2JgAFPf\nTnyGWWBbDIKIrI7Cb5yNJ3Ilw7EPMZj0KQaTP8Ng8j+O/fUmfJp97Un8eG8079an4jcWEKMdJKLn\ndWyNP0Q7XIbFYuGBBx5g48aNDA8OED+wG50xgLpLRA5O39cURWHbtm0MDAzwwL33cG+ejdNtbtrc\nanym8cy/qgsevB6F4oUGcvK1xCVKnGxZy1B3HxpX9dgzd3Z2TnvPC50uzna4eKggGpPmzrgxV6SZ\n8QYVzi7/IETZuPDSK/zyeAdFcQY+tyhhbLXV3R5ErRH47v0pPFYcQ3l/kK/mf4pT1lnhTPD+njvS\nvvcSMzUYGXa7vZowrfbfAT2w82ZKtDocjleB6wtubwFKR/eXA8V2u90C3AWccTgcV3pgKXBHZCwH\nh528+JcqBtxJLI1q5CFjMndLn6fQn0htmY99747QdmIZxuYvoUGh+NKzDEk2WufaebhxBxFakefP\ndY8NzN0jAdqG/CxKN7Fig4mSpQYCAYUTh0bw+64hlGXOAnMEypmjKC0NKBfPIB/dS+idVyjb3khj\nII1Dy35EpWbR+PNmAJUo8IGCaBoHfZxquz2/pnD/I+D3obz2B5SThxCWrEUwmOh1B9hd72RdZgSx\nplt3EfV2BZFDEJ8UvkZCQjx9w8dBkCk74UaWFWRZob7ahzVKxZxsA/+6Komn16Uw7AtR1nln63Nf\nwf+c6abPE+SJpYk3rJZ4I1isKlDCEwOAvp4gijxzOm0wGGTXrl0cOXKErKwsHn74YebOnUtLSwvd\nXV2Yu99AQWA45n1h0sYMUVpaSkVFBflzFjJvw6fxp36YvvSv0ZfyRQKaBEx9u0EJIQgCeXl5PPbY\nY1gsFgZdp/H7FWrKvdNev6enh+7ubpYvX05GRgb3zIpEEmRe6izEr7+qPNTfE6Sxzk9GjoZIm4Qg\nCMxdbEBrULHv8vtRt+9EUAIkJCTQ0dEx5f0UReGPZT1EGyS2TKPYfLsoiDUQoVVR2jZE2yNf5EfJ\n9xInu/jXlUlj9HZZVujuCBKXKKFTq/hAYTQ/35JBQoSWZ7LtvBS1iOBz/4Yy7EQIjiAG/z4zF2Y6\npfkV8BWHw/Gu3W7f73A4hu12+2rCrKnbKdEay3gjMjS6bartE2C32z8NfBrA4XBgs90cGXmwrQ2V\nZGOzqCOj08yqfD06bSuyAu6QivqYaDTLUkmJiabpuUOcjf4cbmM8KmGIe1LO8cmlGfz0QD2XhlUs\nz4ziaEd4xrMuP5mYKAMxMZCS5uPNl1ro7pCYu+Bq9rRz4Qq8+95BPls6tq0tbimDRRvJHzpEYP4m\n6uq8tDUHKV4QSV6RdcY6+O+PjOKVin7eqHayuTh9Up+yJElYI6Noc3pp7HfT2O+hddDD/YXxFCWO\nurJsNpyrN+E9sAOAyPd/GLXNxh8P1KMAn16Zg81y64yl6vNdaDQiuXnxY6J+tpgIUNcx2J9LZ6uE\nySThdjlZsiqemJiw+25tVDTPHu2geiDI+xfM/DeXJOmm+0hpYz+76518eH4SK/JSbnzCDaCW/Jw5\n1owSMmCzWaiv7glrO82OQ7qBMXI6nbz66qu0t7ezbt06Vq9ejSAIREZGcvr0aVyNu9FG1yKnP0pU\nfPaMn7empoazZ8+ycOFC7rvv+rhaDOhDiJd+hY0GsC0Z27N48WJ27tzJmmWraKr3M6ckjuiYyVlj\nJ06cQJIkli5dil6vx6bIbIzZy7u92XzKYsOiUxMKKRza1YzJLLF8TTLqa3IVNtxj4Z3XWjhct5JN\nicfJzs6mrq4OjUaDxXLV9XrlmffX9lLb5+VrG7JJir+xesAtQ1FYm1TOjkaB+n4BtUbNN0ufJWHl\nN9HOD9cb72z3EPA7ycmNxmYL92GbDX6bHMuz++pxsIa6/gS++ty/kPqQFZVWQNEngbUAxVoI5mwQ\np56Y3Uq/vhXM1GCoHQ7Hu6P/vqJW6xrNx7gddAPX5rVbRrd1A9nXba+b7AIOh+M3wG+utG2mWkRX\nYE1KYkVxBcO7y6mP20THpUGWx5SSmhWLNpjAHH8PHSM+TrxwivrYD6OVQuhjavF05tCZvYBlCRIv\nmtX84lAd2aYMDtd2YjNIGEMuenuvzn5jEyQqygaITw6NcaWVuz+AkJCKYI6ACCshUxQ1J/VE6EQy\n7fchCAKJmWoqz3s4dbSPirIB8op1JKbMjMnx4OxIfn2yk83/dRy9JKCTxLE/tUqg36fQMuDmWokh\ntShQ2tDHv2/JGKNcKhsfhEO7IKcApzGCvuYO3irvZG2GBbV/5JbZGYqs0NQwQky8RP9A39V3FRtL\ndfVZFhQVcO5EHzq9iMkiYjB76O29OostitNzvLGfnp6eGVNRp2OGXQ+/38+wN8gPdreRGqHhwRzj\njM+dDoocZoS1tTqJjPHT0jBMpE3F4OD0IcLe3l62bt1KIBBgy5YtZGVl0dd39b2VFGVTZN6LR53M\nsKoAentn9LzDH551DAAAIABJREFUw8O89tpr2Gw2Fi5cOPnxSiJRmnhofpt+MkEID+QpKSmIosiA\nqwy1ppDDe9tZvn5i0DsYDHL+/HkyMjJwuVy4XC7UnkY+FHued7vTePHEZR4qiKbmogfnQIDFq4w4\nh657HyIUzDNQfiaT82ePEJMZ9opXVlaSnX11uLDZbHR19/AfRxpItmhYGKN6T363SaGEMPe8yQZN\nC1vlu+jzBvnBqgjiaswM/uL7iN/+BYLRzKVKD4IIWuP4PizIXp7IqGa2v4P/y2y+ov8IX9u+ndkf\nXY8ucBl1x17Ejl0oghq/PguPdSl+w6wJzbiZfn09EhOnzlC/HjNdWwujK4ox2O32BTfTqCnwDrB0\n9HpFwPnRLPKdwHy73X6l1y3l9lYy0yIlv4Alj6xk2ZnvoQp42evcwoGTMv7QW3S1dnJo9wB1cetJ\nivax5v4YimOCKMjURSUiiQKPzY2hxelnd/0gFzrdzEswTvhgsvN0+H3KOP0jITIacc1mhPnLELLz\nudxnxetRxqmrWqwqlqw2sXi1EZUEZ4656e68jqCmyEi+DpDHb1+fFcHjJTGsSDVTGGcgyaLFqFER\nlBUGvUGSInQ8MDuKJ5Ym8Ozdabxkn8Wzd6cx4pf5eWkH8pW6zrGJiP/0FOJHwwUW36jsJ6QoPDxJ\nEPFm0N8XCmvqJI2fOSUkJBAIBEjK8CCpBdwumezZugnvdG68kT53kNZppNtvFR0dHfzud7/jz3/4\nb4rbdlDYsY9XX36JrVu3smvXLnp6bt3fLIgClohwbQyvR2Z4SJ5R/OL48ePIsozdbicrayKrZnVK\nGxpJ4WBr+tiAfiOEQiG2b99OKBTinnvuQZKmaIcg4opcgxToRuuqHNtsMBjIyMjg0qVKcgu1DPSF\naG2cSKBsaGjA6/WSl5c3tk07cpFs0zDFcTreqRlgYCBIbVU4KXOq4lZpWRqSUwXOti9H11fOsgw3\nrp6a0QD+Vey97KRtyM9jc2PGmII+79W40XsBIeTF2v4H9EOnyEnL4+4sA9/POUKJ6iDiJ74MI06U\nP/8nECZ22GKlcXI1hv69RDc8g6XvbR5M6uAny/34TJE8GftBtr7bT2/CJ+jN/BaDCR/FY5mP5GvH\n0vEXBPn2yiPcDma6wvgKsN1utw8D0Xa7vZxwMaUtM73RqMF5DEiw2+3fBH4K/F/g2dH/zwY+AeBw\nOFrtdvuzwHN2uz0E/LfD4aid6b1uBZr8YiIfuo8Vv/8WtYUf4XLMajrKcvGLBlRaPyvjjhO9dC4h\njUB0UzsqlYZ+tw1ZCbE0xUyuTcfvznTjDynMS5zIoImOkYi0qaiv9pKWpZkgLudxy9RVeUlIDrOt\nrkdsvJrojRIHtg9Tdd5LTFzYt6vy92Lufg2NtxFZ0OA3zsZnKsRvmIUkankwb+pBfbJZSXqkjsdL\nYvnN6S7erh7ggdFqZFdkD/o9QXbWDbImI4J48+2p23e2BhBFiLlucLgy4+npbadkST5tTQGS0iYO\nIHMTwrTlsg4XKTeRPHcj9Pf38/bbbyNqdFxSZ1BsU5FhEvB4PLjdbjo7O+nq6uLRRx9FNYmS6Uxg\nsaroaA3MWA7E4/HQ2NhIcXEx0dETf1PNSCUmXxVlgxkcP99E/nwvOt2NXYXHjx+ns7OTu+++G6t1\nevVBn6mIYP9uDAP78RkLxuIj+fn51NfXE6QNa1Qslec9xCdJ49xJVVVVGI3GqxpQioLWVYFfn839\neTa+d6CV0qMjqNUCBfOmpisLgkDRQgtDA70curSGTdmvEmc6gtxwDr8+g4AhE692MS9e6CXXpmdx\nsglZVig/4xml6IYFKvV6AZ1BRKcX0RtErNEqoqIlpBnqj4mBAawdz6Py9zAU+xBeywI+awNDfw66\n/j24k1biv+8RlK0vMFSwEtfwbDJyrvZR7fAFTP178BnzcUWuIahLIQv4WVyQn7xxlv9QCnn19Rre\nVxTHhqxctMY8vOYSolp/jW7oDB7rsqkbdwcx00zvM6P1MO4Dkgir1W5zOBzXB7Gnu8ZB4OAkuyat\nC+5wOF4AXpjp9d8LiEvWInW1M3vb74lbOsJF5mFRulibpxBhiiDY/Eu8gUSGzl0kNnElnfrNNPVc\nICN2Hh+bF8vXdzcjClAcNznlMnu2jlNHXLQ3B0hOHz/YVpd7UJRwVbSpoFIJ5BbpOHfcTVuTjxzr\nGUx9O1EEFSPRm1EF+tC6KtCNXEARJPyGWXhNRfhMc2Y84wS4Z5aV850u/ljWTWGcYUxtF2BrZR9B\nWcFeeHurC0VR6GwPEH3drAsYY8BcESKcqphQnElDvEnN+U4X902hrHuzGBkZ4c033wRB4JSpBJPZ\nwsfvSh8LXgJcvnyZbdu2UVFRwZw5c27pPpYIFc2X/bQ2+cdKcE6HK7VCrp2hX4EQ8mDueZOAJh5N\nxgMEj79MeXk5CxcunPaaDQ0NnDlzhqKiImbNmujmmHgjEXfkWizdr6Jx1+A3zgYgLS0No9FIZWUF\nq1akcXj3CDUXvRSWhA26y+WiqamJkpKSsSQ7ydeOKjiIK2o9JWYjy/QWQi7IKtHcUAxSkgQWrori\n+EEX2y49ilG1i/uXCWh9DehcF3n+fCP9nnl8dUUioRCcLXXR1R4kPVuDVifi9ch4PTIet8JgfwC/\nb3TVIUCEVUWUTUVUjIQ1SiIYUMLilu5RgUu3TMDtZUnc64hGJ4OJjxMwXHWHua0r0TtPYOrbzsBd\nn0S5cIquIxWQPnssUVMMDGLueYOANgVn/KPj6MRReonv35/HmR/9mFez7+I3p+Hli73cPzuKzTmJ\nmLXJ6J2leCKW3NQ3/V5hxjy+UVfRn6/dZrfbH3c4HL9/z1v1N4Rw/6PQ1U5k6Sus+lQawoIVBNta\nEfqcBJsz0CVdQvd+C/PcPrbXQn19JfnqEebrDKxJNuCSdZi0k3/8cYkSZotIXbWXpLSrEhCDfUFa\nGwNk52kxmFQg+1F7Wwipo5Al6zimS1KqmsvVCpfK+piTvx2/KZvh2PchS+Gs7mHlAdTeRrQjF9GO\nVBDhqsTl78UVvWHm70AQ+MKSBL70TgPPHmnjp5vTMahVDHqCbK8dZHW6hYTbXF2MDMm4R2SyJlFm\nFQSBhISEGQkRzk0wcqBhiKCs3DAH4Ebw+Xy89dZbeL1egrNW09cl8o2lCeOMBUBGRgZJSUmcOHGC\n3NxctNqbX91cyfju7QqSmHpjOZCqqipsNtukgU3D4CHE0DDOhMew6eJIS0ujrKyMefOmziAeHh5m\n9+7d2Gw2Vq5cOeN2e81zMfbvwdi/D78hNyyLI4rk5eVx5swZpHXhFXRjXVhixGJVUV1djaIo5Odf\npc5qXRUoiPiMeXS1BcgLGGhRfOypGeD7qalTfkNjz2xSsXy9icN7+hkZ2cTR9iDFJXbcri5eON3N\n0qgecizZHD8wwkBfiKL5etKzJ/+dggGF/r4g/T1B+ntDNF3201A70c0piqA3gN8T5KRvJUs3RCJr\n4647SIMragOWnjfQemvw/cOX6d7agtndjr6pAfKKsXQ5QJEZiv/gOGMxdgmTmflLiijZ+mOqPv8T\nXu3X8aeyHl6v6ONjs1fymOFFNO46/MYZGPn3GFMaDLvd/tQMzv848L/LYAgCfPyLKH3dKM//HOXI\nbjxV53Hf/Si69BJ6fDkY4jqJ0behbhpkeCCVQM+bRIlqfpAIiqhhZOh+vOaSCZRGQRDIytNRdsI9\nSrFToygKF8s8aHUC2Xk6hJAba/vvUftaAZBFLUFNAkFtPEFNAqLsZUnsJXZe+gBlno+TmpM1/j6C\nSECfSUCfyYjtXixdDgwDB/Caiwhpruvc08CiVfGV5Yl8a28zvz3dxRNLE3mjqp+grPBw4e2zMTpG\nC79cH7+4gsTEROrq6hgeHsZsnlrvf268kR21g9T0eiiYIrN+JggGg7zzzjv09/dTvGoTz5bLPJgX\nNan0hyAIrFixgpdffpkzZ86wbNnNuweuFFOCG7uj+vr66O7unnxgl/3onSfwGfMJ6sKJXyUlJbzx\nxhtUV1cTHz9RqywQCLBjxw5CoRCbN2+eOm4xGQQV7sjVmHveRO25PCblkZ+fz+nTp6murmZOUQkd\nrQFOHBph0UojlZWVxMfHExl5ldqqdVUQ0KfT06vhbKkLa5SKpDwjew8P8J0DrXxnfQq6GzDGtDqR\nxav0vLu1gea6ZPyKi5e6vbhCGv4h9gLHdufg8upYsNxAQvLUExxJLRAbryZ2dCUrhxScAyGcgyE0\nGgG9Mey20uoETH3baa4d4VjzJjr6jMRNEi/2WuZjGDyKqW8HnYZ/ot9qYFbXbuTn/oTpQ8vQpDkZ\niv0AIfXUq3Rh/b0oe94ib/+fefrL36Guz8vzZd3850WZkqIUsp3H/iYGY7pf5LNAxg3+/nYKcHcQ\ngkaL+PmvQ0QUdLUj3P8oQyvXIEhqLBHpDMfbGUj7MvEpVlQjuRzXFdCX9lUGkz9DUJuEpftVLF0v\nI8gTeelJqWr0BoG6qvC+jpYAA70hcgt1aIQRItt+i+TrYCDqQYZiHsRrngco6IbOYel5A1PfdmLi\nJGJiofJyzPR1fQWR4Zh7UUQtlu7XJwQGb4TCOAMPF0az7/IQb1X3s/3SACvTLCTNUJl1OnS1BbBG\nqdDpJ++CV+IY0/HsAYriDYhCOI5xq1AUhd27d9Pa2sradetxNEvEGCQemaYKXVxcHLm5uZw7d47h\n4Rl7Zseg0Yro9GFDf6P63dXV1QiCQG5u7oR9+qHTiLIHt/WqMUlOTiY2NpazZ8+OK3kbDAY5d+4c\nf/jDH+jo6GD9+vXjBvGZwmOeT0hlxjiwf2yb1WolMTGRyspK1BqBJavD1NGje4fxuLTjVhcqfw+S\nv5uO4HxOHnFhMIksXmWkJNnEPy9PpLbPwzOH2giEbtxfzRYjXs4xKPTTWR8kZVjLUyuzudD8ED4f\nLFsemNZYTAZRJRBpk0jP1pKYqiEyWkKnFxEVP/qhk6SlyRhM4qgbeZLvT1AxYrsL0d9Hxel+dHqB\nzE/dj/rBzZiSB/Fc9uJpm34FJegMYWHCyjKUmotkR+v415VJRGhV/LhxBZLrEir/HWJ+TYPppha/\ndjgc353uZLvd/q33uD1/NxAskYjf+TWIIoIoIgPDsoClsxvX8Ah+s4nEJCMt9dDc0U9xkgG1PprB\npE9iGNiPsX8vam8LzvgPEdRd5e6LokBWro6L5zz0dAaoPO/BYhVJT/EQ2fY7xICTI5126stSWbPZ\njGFU3RRFQQwOIIbcBLVJ5OlDHNo1Ql2Vj7ziqYOEisrEiG0Llu5X0DtP4LEuvan38MFCGxc63fzu\nTDcC3HbsAsIB/sH+ELOLpp5v2Gw21Go17e3t0/rXTRoV2VE6zne6Ji33eSP4fD5KS0upra1l+fLl\nVMmxNDt7+MbqpBvOcJcuXUpdXR2lpaVs2rTppu8dGS0xMhxCb5j6PrIsU11dTVpaGgbDdSsoRUbv\nPEpAm0JQnza2WRAESkpK2LFjBzU1NURFRVFRUcGpU6dwuVwkJyezdOnSMXmNm4aoxm1dibnvXSRP\n09i9CwoK2L17Nx0dHSQmJrJig5l973YRb92A4Rq3ndZVwaA3ikPlmWi0IktWm9CMxi2WpVr4/GKZ\nXxzv5GfHOvjq8sRp9dCGvEHK9AVc9vvZbPaR5dHTVjqCTq/jnpwXsIREBpR/fE/8/bqhU4iyD2/U\ncnILw7HE9uYASZPUEPEb8qgcXMfgkI75SyTUWgFroQs5YMRZ6kR55SmEtfeES7jqJv9+hTX3oOx6\nE3nrC4hPPoNRo+If5sfx06PtvNE1m3uspYzETC9e+l5D9fTTT0+64+GHHz50o5NncsxfGU/fymwP\nwvRAt3t81rAgiuN8y36DAf2AE+3wCO7oSHRGFfU1XkK40Ua1E20Iu4fCLqEstK6LGAaPgiAR0KWO\nuY7MESqa6v309wRxuxQWLAiSNPhbCLjYfulhOoZTkWUIBbmqaCoIKCo9smQBQUCnF3GNhGhp9JOS\nrpm2ulxQE4/kbUY3fAaveR6KSjflM18PURAojjeyv2GI5WlmNmXffsZsW5Of7o4ghSX6KbWTBEGg\npaWFwcHBG0pY97gCHGka5t7cSDSq6QcGvV5PW1sbVVVVlJaWcvDgQTo7O5k7dy7pBSU8e7SdRckm\nPlh0Y+Oj1WoJBAKUl5eTkZGB0TiR7ODxeDh48CB9fX0kJSWN22eLl0hO00xbw6ClpYXy8nKWLl06\ngR2lcVViGDrBSMy9E9yNkZGRVFdX09jYyLlz56ipqcFms7Fx40aWLFkyrZtvJghqE9A7T6IK9uMz\nzwXCq4zz588jyzKZmZkIQoiDR14lwpxMd5saQYCoGBVC2wF2VD2IImpZttYUjttdg8woHQa1yFvV\nA/R5gixKmlzM8FyHi6f3t9LtF8lyXeKzmzOJjDQgSRpKluoxRmgwOEuRRd04g3pLUEJEdDkIauJx\nR63DHCHS2RqguyscTL++fX6/wrHTkcQZmpmXUYPOVY7GU48z8ePIq+zg96PsfwflwmmEeUsmNRqC\nSgK1Bg5uR8icjRCbQGqEhuoeD7s6o7nPcgQheiEI0oy+5akw2he+PZNjpzQY/4/iPTUYEyAIBDUa\nTL19CIpCwGLCOSjjGYig3/wiOVEbxjqOrLbiNc9HFejF4DyGxl2NFOhDCHkQJA3+oJbO9iA2W5DF\npv9C9gd4t+aD6OLSWbjSSMCv0NzgJyVjamMQEamisdaP3z8xl+H6dgf0aRicx5H83fhMxSAIM+5k\nRo2Ku7KtLEu13LBu80xQXe5FAHILJ+ZWXAun00ldXR3z5s2blr6qEgT2XHYyy6afQK/1+/309PTQ\n2NhIRUUFO3fu5OTJkzQ3N6NWq8nLy2PZsmUUFBTw3LFOet1BvrU2GYN6ZnTZuLg4Kioq6O3tZfbs\n2eOep7Gxkbfeeov29nba2trIysoat0pQqYRJjYUY6EfytSGrozh+/DgjIyOsW7dugoy3uft1QGQ4\n5oEJM2hhNBhdVVVFREQE69evZ9myZURE3LiU6owgqECRMQydJKiORlaZENV6hoaGqK2tpbi4mIaG\nBmpqqli5Ng+N2kTDJT+eYR/VDbH4ZBNL1lgwR0z+nmfH6JEVhbdrBqjs8XC8ZZg99YPsrBtkW80A\nb1b183bNADFGiS+VROCsPEpcXBzZs+IpmhdHIOghpIlH8rWjHz6Fz1SEorp1wUitqwL90CmGbfeG\nZeIFAb1BpLHOj04vYo0a76ypKPMw0Cezqug8kd5jqH2tuK2r8UYsRJAkhMIShIxclIPbUU4fQZiz\ncEwRehxS0sNVAS/XIKzcFHZN2vRsu+Sk26dhdcwgI0oSOp0On396aZap8P8bjFvATAfPkE6LyufH\n2NePfmAQj05Pe6cWt/EYtoh4TJprJAhENT5TESEpArWvA62rEp3rAgbnMbp6NHSPJLA2+UUkfOxv\ne5Ss+RlkztIhSeHazw21PuSQMq5uwrVQa0QCfoWmy34SktTTKp0qKj2KqMbgLCWoiSWkjZvwzMPO\nEKUHRhAEJnwAGpX4nhiLgF+h/KyHlHTNlMlZVxAKhaiuriY5OXnagS5SL/FWdT96SaTIpubMmTOc\nO3eO0tJSjh49SkVFBQ0NDQwMDJCSksKcOXNYu3YtCxYsIDU1FYvFwtHmYV6r7Ofj82KYlzDJhzsF\nJElCkiTKy8uJj4/HarXi9/s5dOgQhw8fxmKxcPfdd3P58mX6+vomGJUJkANEtv0nBucxPKp4dh48\nR25u7oREPcnbjKl/D66oDVPOnmNjY1m4cCFFRUVERka+54WZgpoEdMPn0A+fxTh4GJ3zJOmRXrSh\nPkTZS0tTHWoxxNIl84lP0oCgoqEuRFBWs3Q5WGOnf89FcQZCMlT1ePCOChtqJBGLViLWqGZ5qoUn\nliaQFGWirKwMrVZLRkbG1X4tCAT0GeiHTqL2tkxKRJkpLF2voYgSIzH3j13DaBLp6QrS1R4gPUs7\nlls12B/kwmkPGbO0JObEo3eWEtQmMhRvH2fYhdgEhNlzUI7sRjm+H6FgHoJlfC6MIKrC1KyD21Fq\nK1F2v4mp7DCyKPFWcDbzAkfpOClyoixEZp7hln7jmzEYfz1t6P9FGExNxmONwNLRSd5IG6dJxDa8\nhrr+PcSbCscfLAh4IxbijVgIShDJ14Xf2UlVdzrpUfWoVUGqlMeZtzZhnE6UwSiSkq6h+bKfnHzd\nlMHhnHwtzQ0+qi54WLxq+g/QE7EM3fB5zL1v4zdkj9s30BfkxCEXAb9C5XkPCcnqMb/ye4nuzgCK\nDHHTrYhGcYXh09HRcTXhaxKoVQKFsQbOtw/xdvMR2tvbiYyMJC4ujvz8fKKjo4mOjiYiIoKYmJgJ\nyYouf4j/Pt01abnRmaCwsJCysjKOHDmCWq1mz549OJ1OSkpKWLJkCZIksXjxYg4dOkRTUxPp6elT\nXss4sA8p0EdIsmLtdmBWR0yae2EYPIIs6vBaphZcEASBuLi4OyaLoah09Kd9BcnXhuRrD8/mfe2s\nyhpBFA5RmAVkAU0/AiBGJ5CWnYVap0OV+OEbXl8QBD4yN4aPzEAdOD4+flKChCxZwmzB7lfRDx7F\nb5yNKtCLyt+LFOhFFehFkP0MxzxIUJc0yZVB8jSh9rUwbLtv/IAvCOTN0XNs3wgNdT6yZ+vCrMez\nHjRagdwCHSGNnoGUzxOSrCBMHG6FrNmITz6D/Ny/If/4a4hffAoha/bYfsU1jNLaFP6f6gvhOjSh\nIO/rPc1hQwo/61jEJ/X/H3vvHR7Xfd75fs4503vFDHojCJAECYpNIiVKJFUd25IsWyNbTuzreFN8\nc5NsitN2b5InebLrZDfZlJtsnE1iJxvbm7Fs2ZYtSlShSImixA52Er0N+hRMb+fcPwYECWEADkCA\nVMHnefCQGJw5v9+ZOee85/eW75vEOXoZUSw9PXqplLTC8Pl8/+3pp59+pcjrbz399NP/vBITWyIr\nvsIAQBDI67QknA4EnZqx4SzqtJetujiKwYqkncc/LIjIKgtnL9mYCivctbcWxbsTh9cyp/IbwGwV\n6enIoCjM+zQuqQQEoK8rMyOhbjSJM0J+7513TleNPnwEMR9DVbaNRCLB+GiWdw/H0WhENt9tYLAv\ni5xXbroCWAxyvrASunw2hSQJtN4gfzIfKpWKrq6uOZISxYgks4TPv4UcGeWxxx5j3759NDU1UVlZ\nicPhQKcruL+Kfc/fODXGhbEkv/dAFS7j4o9ZFEVMJhNnz57l0qVLaLVaPvGJT9Da2jrjRnK73XR0\ndNDf3z/r9RuR0sNYRr9LyryFqOfTqCffZq0ni6nhEQTx+s1GzAYxj/+ApHXXTPHcfNyKb7skBBWy\n2k5OV0PGtIGU9R7e7rNy4MQYl8d0lDU/jGJdT0ZfT05XjdGiQyi7C1m9PIWW14hEInR0dLB582Ys\nFsusY85pylGlBzBMvYMhchRdrB1tsgMpG0QRdYi5CProadLGlqJuK9PETxDzUaY8vjl1EwajSDiY\nI9CfpbZRS2AgQ29nho1b9dhdhe9MVpkXFA4ULDaEu+5BOfU2ysEXEeqawOZAeeWHKF//U7h6HtZu\ngMlxhCc/j/T0l1Dvfpgqt4UfdWZwmSe458HH0Bvy846xECuxwviyz+frmBb6w+fzlQFfZ1oH6iOL\nIJB02nE0JrlyPo01W429e5yEPUe03IOsmZs9EZ3K09+ToX6NBqNpYT+50SRRWaumtyvNmnXaeV1O\nDc1aFAUGejKcOZbg3Ckor1JTXafBWaaadWPOactJ2O/HGHoDOXKJ4UErp44mMJoL2So6vUhNfaHw\nqq5Ji8l8az0EZFlhsDfD1QspkgkFu0tiw2b9nIZS81FeXs7ly5cZHh6eN6tHURTknhO4s+N4Nuwo\nrWqZQr/lb58dZ//VMD/VbF9SB71rNDY20tLSglqtZteuXbOK+bTRMyCouO+++/jxj3/M+fPnaWtr\ne89ByFjGvo8iGYi5PkYknufHpy18YVuI1MQPiZY9PeMKMYSPAMIdk4e4GWtbNvDW2+/iNXqRPLtY\nmmd9cVw7N0ZGRuYkFyAITJU9jX7qOLLKSk7jIq92oUiFeJKUmcA29HVsQ/9EqOoXZhkzMRtEG79A\nwnY/iMXTc1s26jh8IMaV80mG+rPYndIcJYebIbi9iL/9NeT/8YfIf/PHYLZCeLLQOvapL0BFDfIf\n/SrK/u/BjvsB2FxuYZf9Kj8MVvG4IQQsPUZTKqUajP8BjPt8vm8DR4A/oNDT+ycrNbEPEt5KDVfO\npzmgTLJG7OOu0Db04TBxt5tYmRtFdf2me+VcCkmCpvWllbA0rdcx2Jel60qa9fOkz4qiQNN6HWvW\nFcTfBnoyBAYyDPZm0RsKzZ2cbhUOtwqDUSRu34c2do6ud45xoute7A6JHbuNMy6o5lYdQ/2F1cC2\nexc+CdMpmXhMRpIEJFUhkCtJhVz2kcEsVy+kiMdkrHaJTdt0uL2qRflZN23aRE9PD8899xybN29m\n586dcwrNjhw5Qn/XVYbNa0hpSpMfH4ik+YsjAbpDaR5ZY+WLt9gUSRCEoqm1+tBhzJMF3cwNzo9x\npqpqpkL8Rq0nfaQQGI14PociGbly5Tgd4zqCpt04o2+S01aTtO1EyCfRTZ0gbd40U93/fsNgMJSk\nTbWceDweBEGYt25HUZlIOPYW/Vte4yJc8WXsQ/+AfegfC0Zj+rMtGGdxQeNstauoqFbPVIffff/N\nV8/FECx2xK/+CfLX/wzSKcT/8OsIzdczBIVdD6J8959RxkcQ3AV37TbRy1kxyN+81cF/erht2eNU\n76VUg/Ea0Af8MvBfgG/4/f7/uGKz+oBhtoroDAK61D3EGmS+NfYttme2sm5sA4bJSWIeD3GXg3BI\nZngwy9oNupJbcZrMEpU1ano70zS2aBfU2REEAYdLhcOlovUuPSOBLEN9BeNxTXhNbxBwuFXohGfp\n6jXgdU6P75JGAAAgAElEQVRx157qWdk6Or3ImhYdV86nCI7ncBQRQwSIhHIcfaMQ95gPi1Vk+31G\nPBWLMxTXcDqdfP7zn+fIkSOcPn2anp4eHnrooZnCvpMnT3Lq1Ck2btyIom3m2FCMvKzMm7uvKAo/\nuRLim6fH0KlEfu/+Su6uvrUU0/kwBN/AFHyZlGkjIGCe3M+nt2/nr55Pcvz48ZnK7UKHvAOkDc2F\nbB5F4dKlS1RWVpL3PkZ6eALTxI/JactRp/oQlcysQr33IzfKjd8OtFotTqfzpoWe85HXeglXfAnb\n0D9iG/pnxj1forOrm3t1J0iZNxXS2RegeaOOkaEs1fWaOQkji0EwmJB+7Y+K/61tR8FgnD2O8OAn\nScTyJCImPl95kY64QCaXRau+9aLahSj1yL4PqIFvAp8AfD6f71+ATX6/f37Bmo8IgiDgrVAz0JNh\n665HqLXu4vz485ya/Fd25/dQE5DRTQY5OlyORisU1U9aiKb1Oob6snRfSbNuU2luE0klUFmjobJG\ngyIrTEVkguM5JsdzjI/kyKQN1HtGuL/yO4SVX0Vmtk+5oVlLX1eaC2eS3PfQ3Dz4qXCeo2/EkVSw\neYcRRVHI5yCfV8jnIZ9TMFlEvJU310m6GVqtdiYm8dprr/Hcc8/R1taG3W7nyJEjNDU18cADDyD2\nRXm9Z4ruUKqoeymUzPFff3iRd/pCbK0w8sv3lGPXr0zehyH4Gqbgq6RMbUx5ngYEFFGHe+oYX9xd\nwb8dOcPGjRuxWa2Yx691yHsSBIGR4WHC4TDbtm0DQWTK8zT2wb/FMvJtQCCjbySnLb2HwUeFa+7L\nG6vbF0NOV02k/IvYhr+BquNvyA8JiGsyJEswziazxIOfsKDVrdwTvuCpAG8VSvsxePCTjAQKMct9\nG9r4Qo2bidjKixGWerXIwMf9fv87079/0+fzHaC4+uxHkrIKNb2dGSbGcnjKzWwt/wIR+yBHRr7N\n6egJNgefYWI8T0VzgAx5VMwN+imKTDw7QSQ1AIJAhekuBEHAbJGoqFbT25GmsVm76OwlQRSw2iWs\ndon6tVoURSGTVqhwOxDOgHn8R0TKvzgr5VClEmhu1dF+PMnwQJaKmutPLtGpQvqtJMGuvaabxmKW\ni+rqap599lnefvtt2tvbZ157+OGHEUWRtvKC++zMcHyWwRiNZXilM8JLnWHSOYVf2O7hY022lVm+\nKwrG4CsYQwdJmrcQLfv0TGZN1P0ksmSgiTfwbTZw9O03eXJ3FdpEB1OuTzI4nqCjo52Ojg5UKtVM\nKq0i6Yl4fxrH4N8hKFmitk8t/7w/BJSXl3Pu3DnGxsYWp491A0lNDe/0NPBIzVX2rIG+sAFdo5dS\nzpT5MhmXE6FtO8qrL6Ak4owOFR7KdA4P6FwQW3mpkFI/1d+6wVgA4Pf7Az6f7ysrMKcPJK4yFZIK\n+rsyaDQCRpOIVVfF/bVfJRBt59AhPSZVjhblCj++8jVMWg9lxg2YNR6m0gHC6QGm0kPkbtCfavN8\nlhZXoeVI03odgYEsPR1pmluXHpyFwopIqxMQtA7ijocwT76IJn6JjGn9rO2q6zT0XE1z6WwKT6Ua\nSRKIRfMcPVio1di55/YZi2toNBr27NlDU1MT3d3d3H333TM3B5tORb1dy5mRBE+uUzg2FOVAR5j2\nkQSCAHeVG/n1B5sxySuUNaQoGCdfxhg+RNKybbqn9g03EUEg7nwUWTSwgRfRqU6gHznBRMbGP37v\nIrH4CSRJoq6ujk2bNs0KnOe1XiLeZ9EkrhbtuLbK9cD3wMAA9fX1i37/NQHKvr4oNVW7aRbe4bUr\nOjaVDcxK685llZL7ZiyFa/pUxR5ohE07UF5+nlz7SSbHN9HYsnx9YEqh1H4Y/+bz+XZRaICkBX4V\n+ALwdys4tw8UklRwSw31ZxmZVmJVTxsOtWYNyUSOHetyNMlreFr7Fd5UH6Ev8hY5OY1GMmHTVlNv\n241VW41VV83VyZdoH/13TBoPVZZtWGwS3ko13VfTVNdrMRiX52kmaduFPnoK88QLTBrWzMoEEUSB\n9Zv1vHMoTm9nmvJKNUcPxlCUwsrCZLm9xuJGKisr52bDAG1eIy9cDvLl5zuJpPO4DCo+u9HFg41W\n3EY1LodhVuvc5cQYPIAxfIiE5e7pAq/i31HSvpscGuqVHyAr8H+O2/F4y7l3zRrq6+vRFMmuA8gY\nW26aRvtRxmKxYDAY6O/vX7TByOVyvPjii/T19bFv3z7cLa2MZR8icPCbiOfPzxiMiekU9NYtemob\nV+ZmffytOIoCO3bP7dxJYwuYzKSOHUPxbsI7T1HvSlGSwfD5fL8A/BbwAnA3kADcFLrm/fqKze4D\nxua7DTRtkIlHZeKx/PS/hd+dZSrKWq1ER3JUjsFPeX+GqVonmXwcrWS5fmIoCupkkkrDM7ycCfPO\n4P9kX/1/xqGvp2Wjjrdey/L261F2LpcrSJCIup/APvR1DJOvcUFlxGVoxjyt8+/2qnF7VXRcSNNz\nNU0+X1hZzCfpcKfZVWNm/9UQLW49j66xsbncuKB43XKhSgcwhA6RNG8j5n7iphXFWfvd9KfUJGIh\nnnx297xGYpXSudZHZWBgYFHvu9amtre3l71799LaWii+Vak1rFu3jvb2duLxOCpJz6l3EsgyXL2Q\noqpOM6vYdjnIpGVGh3OgwGggN0fyR5AkhNZtaE4fR1cjY3Pe3uuwVJfUzwBtfr8/5vP5Dvr9/jzw\nhz6f7+DN3vhRQhQL8QazRaKQIzCXaLkHKZvFMjKGrFaTcBZiGWImiyEURh8KoU4VevZ+VnySC+J5\n2nv/kbvX/AZmq4Ode0y8cyjO26/HuGePaXqsWyOrryNh2sKJiR9xTo5hUDt5qP4P0KsLVc/r2/Qc\nOhBFoWAsrPb3p7EAaHbp8X92rgz4iqIomCZ+giLqibl+qmT5CUP5FpbewWOVYlRVVdHV1UVHRwdN\nTU033f6asejp6WHPnj1zhC5bW1s5ffo0Fy9eJBdfRzarsL5Nx8X2FIO9mWVfZYwGCsZCoxW4eCZJ\nmVc1pwhX2bgd1TsHqZN6EITlLYC8GaX6NRS/3x+79v8bXl99LFosgkC4poqU2YR1YAjTyCiOrh48\nFy9jGR5BkSTCVZVMrGkgZbXSmtvAs+ln0Fw+hhQJYrNL7NprQlHg7ddjTIWXVt15I4oi80Y+xDk5\nxlq1h0w+zuH+PyebTwKF/tM19Rqq6zTIcqFq+04zFc5z6micVHJpGTHLiSZxGU2ym7jjQRTp1uJL\nq9wara2tVFZW8vrrr9+0T4miKBw6dIju7m4eeOCBou127XY7lZWVnDlznvGRLK136Wlo1mJzSHRe\nSiPLy3stjASy6PQCm3cYiMdkejvTc7YJujciCxLeydPLOnYplGowrvp8vm/6fL7dgN7n8231+Xx/\nCVxcwbl9eBEEQnW1ZA16LCNjqFJpYp4yRtetZaKpkYTLQcZkJFxbzeiGFobt4Mrb8fQM4brSiUOX\nZddeE6IIbx+MEQ7mljwVRZE5EfgGXeE32WjeyiOCin2We4ikBnh78P9DVvIMDxbqOHo6Mhx5Lcb+\n5yMcfSPG1YuFOo07YUCunE8x1F/wJy/YRGqlUfKYJvaTUztJWu++c/NYBQBJknj66aeRZZmXX355\nwRTbs2fPcv78ebZu3Tq38v4G6mrXk0xGMdjGqGkoSJk3rdeRiMsM9WWXbe75nML4SBZPhZqychUu\nj4qrF9Jk0rOPYXhSTdCxDkPXyWUbu1RKNRi/AmSBAxRiGG9S6La3Wry3RBRJZLKxnvGmRsbWNxMt\n95Av0htaVquhdhMnqqY4IO1HyURxdXThEJLcu8+ESi1w9I0YwfHFGw1FkTke+Ce6w2+w3vU466p+\nmZRlC83JTh7QeBiJneXYwDdoP5HAYpN4+HEL2+41UNugIZOSuXIuxZHXY7z8gwgnjsQZ6MmQTq38\nE38iLjMSyOLyqIhG8pw4Eid/h1Y9+qnjqLLjxJwfK9qfeZXbj8PhYO/evQQCAY4fP150m/7+fg4f\nPkx9ff2CLXbTaZmJIQ+SqCWZ7ZiJNXoqVFisIh2XUijLtMqYGMuRzzFTu7Rhs55sTuHqheuZk4qi\nMBrIkmzcCqNDKKM373u/nJRkMPx+f9zv9/8cYAC8gNHv9/+i3+9fel/MVVAkiazRUJLPe43rYTIu\nL/8m/hNpUcbZ3YszM8W9+0xodSLvHIox1D+3cf18yIrM61f+kp7wYTa4n6S17DMIokTU4yNU+Qu0\n6GrZJpnpix5CdH2Xu+42oNOLlFdpaN1i4IHHLDzyZMGAVNRoCE7kOHMswYEfTvHWq1E6LqaIRW/d\nXVaM3s40ArB5h4G27QYmRnOceTdRvF3mCiLIKYzBV8no6skY19/8DavcNlpaWmhububYsWMEArNv\nqqFQiP379+NwOHj00UfnrcdRFIUz7ybIZURaWtbR29tDLFbwzAuCQNMGHfFoQb1hORgZyqJSgbOs\nEFq22CRqGwq6btGpwrUUCeVJJRU02wqrWaX92LKMXSqLys30+/2K3+8f8/v9CoDP53tuZaa1SjHa\nPJ8jr9Hwfe33SRsN2PsHKYuMs2uPEYtN4tTRBGdPJG76tC0reY4P/S8uj77CBvenaC379KyLJquv\nI1T1Fcq1X6IBCyH7YVLhP0fMRWbtR6stGJC27QYeftzC7odNrN2gQ5YLTZIOvhjl2FtLW/3MRy6n\n0N+dwVupRm8Qqa7XsK6tUKNy4fQ8PZZXCEPoEGI+vqhA9yq3jz179mA2m3n55ZdJpwuxgFQqxQsv\nvIAgCHziE59YMDut+0qaseEc6zfr2bptE4qicPHidS98eaUak1nk6sXULZ9311YOZeXqWZlXza06\nJBVcai/EE0eGsiCAc30FVNbedoMxb5aUz+frLuH93mWcyyo3QRLVtJZ9hneH/p7TFcO0aWoxj44h\nZdLs2lPJ5QsZui6nCU3m2brLUFRpNi9neWfw7xiMnmBH3c9Qbyzeizqdhjfb12I0/gGe2v/Gofg5\nPjnwt+jqfruo60UQBGwOFTaHiuZWHalkIWDX25nhyFAMu1OisUWLt0JdslJtMYb6MmQzCvVN1913\njc1a0kmF7qtptHqRpnWlCTveCmI2jCH8FinTZnK6qhUfb5XFo9Vqeeyxx3juued4/fXXefTRR3np\npZeYmpriU5/61IJNucLBHJfOpiivUk+3YNVSXV3NhQsX2LZtG6IoIogCa9brOPNuomgK7GIITeZJ\np+Z2ztTqCufzpbMpxkeyjA5lcbgktFoRuW0HykvfQ4nHwOVa8tiLYaEVRgT40vTP14F3gd+Y/v03\ngZPAn630BFeZTa11JzZdLefGn2Oysoypcg+GUAR3Ty8bNmjYsdtIMiFz+EB0josqm0/xZv9fMBg9\nwWbv59le+2zRMRRF4dzJJLmsQtsOJ7sa/xCDZOVoshN9sLQ27jq9SMtGPQ990kLrFj3plMKJIwkO\n7o8yPFi66+y98+rpSGOxiTjc142WIAis36yjskbN5bMp+rvnZpYsN6bgywDEnMUN7irvD7xeL/fc\ncw8dHR1897vfpb+/n7179xYt+ryGLCu0H0ug1Qm0bb+uPNva2ko0GqW/v39m28oaNQajyNULt7bK\nGB3KIghQVj73Gb5+baFQt/1EkqmIPFOsJ7TtAFlGOX/7gt8L1WF82e/3nwLw+Xxf9fv9n7jxjz6f\n73lg/61OwOfz/RpQCcQpVJH/LmAHvgZ0A03A7/n9/tFbHevDgCCItHme4VDfn9EZeo1mz8fIaTTY\n+wdxdnVDYz0PPGrm5NtxTh1NMDGao3WLnpwS583+PyeY7GJHxc9Rb79/3jECA1mGB7Os26SbLtAz\nsrbsSU4N/wvRyZ+gNW8gf2Mr2gVQqQTqm7TUNmpm5M5PvZPg4U+qFq2JNTmeIxqRZ13E1z+XQipi\nOh2n/USSidEcjS1arPblFxdUpYbQRc8Qtz2ArF58h75Vbi9bt26lv7+fwcFBNm/ezIYNGxbcvvNS\nmqmIzPb7jKg118/RhoYG9Ho9586dm+maKIoCa9ZpOXsiyfhIbslNx0aGsjjLVLPGu4YkCaxr03Hy\n7YJCwcwqpK4JLDZoPwYf//SSxl0s816x14zFNDU+n++9n4SGwo1+yfh8vs3AF/1+/2/6/f4/oGAc\nnqQgof6q3+//GvAD4L/fyjgfNrymjXiMrVyc+BGZfJyU3UawvhZ1Ko2rswejWmbXPhNrWrT0d2c4\ndXKYg71/QijVy67qX1nQWKSSMudOJrE5JBpuUNWtt92HRjRwJh/HMvocKIvLhhJFgYoaDVt2GpHz\n0Ne9+FVGT0cGtaagwlt0DElg+71GGpq0jASyHD4Q4+jBGGPD2eWLbSh5TBM/RhaNJOx7lmefq6wo\ngiDwsY99jAcffJD77rtvwW2jkTwdF1NUVKvnuIckSWL9+vX09vYSDodnXq+u06DTC0VjGYqiMDIy\nwujoKLlc8VhebCpPLCrj8hZ0sI4dO0Zvb++sbcqr1DjLVFhsEsZpV7Mgiggbt6GcP4Uyz76Xm1If\nv14Hjk0HuScoyIJ8Bnj1FsdvAm6s4+8GHgQ+DvzJ9GtHgH+5xXE+dLR5nuFA9+9zaeLHtHmeIW0x\nM9lQh6O7F2dnN5Nr6lnXpicrTXA58xcI6Si7a39jbs/xG1BkpRA0zylsvtswq22sStTR4NjHlYmf\nkEj1oI+8TdK28MVXDItNwuVRzSjvFmtNW4xEXGZkKMuaFi2Sav73qNQCG+7Ss3aDlr7uDD1X07x7\nOI7ZKtLYrMPpvAXDochYRr+LJtXLVNlnUKSVj5Wssjzo9fqbriwUWaH9eAJJJdC6pXgBZmtrK+3t\n7XzrW99i/fr1bN26FYvFwpp1Os6fSjI+mqPMq0aWZbq6ujh58iRjY2NAoZWv0+mkrKyMsrIy3G43\nqVSK82f7CQSH6Ht1clbdyGOPPTbTPVIQBHbsNs55ThM270A58irZi2egom7pH1CJlGowfh34RQpG\nohwYBv4e+F+3OP5x4L/6fD4dkAa2UTAgZcC1Ms0pwO7z+VR+v3+OGfX5fD8P/DyA3+/HtcTgj0ql\nWvJ77wQuXPTG9tIxcYAdjT7MOje4XORtVlRnzuHp6aO3XqBf+zcIpNB0/z84G3fgcl0Xo7jxmOW8\nwpuvjTIayLHjPhf1DXO7pd1t9nF1cj/tKj27g69grNoFutJcUzeyeZueV38yTCyio6GptOZFJzom\nEIC7tnsxmUtb9pdXwPadCj0dUc6fCXPmWAI5F2LrziV8z4qC0PO/EWLtyNVPYap8FNPi93Lb+aCd\n18vBUo/5QnuY0GSe+x/yUFlV/Lx0uVz80i/9Em+99RZnzpzhwoULbNq0iZ0776WvS83Jo1FqmiY5\nfeZdgsEgTqeTxx9/HL1eTyAQIBAI0N3dzYULF2b2KSBg0LvZfvcu6urqKC8vx+/3c+DAAZxOJ83N\n80vdKPc9yNg//HcyJ9/GtWnboo95sQi3slT3+Xwtfr//8q1MwOfz7aOwqhgH1gBh4IvALr/fP+Dz\n+RxAp9/vL0U0RXlvznWpuFwuJiZWXk9+OYlnxnmx87eote5iR+XPzbwuR4bx9I6QUGLs17/O+sqf\n5dybVtIphfsfMWEwFpa01445n1c4+Xac0UCOlk26BbOMjg7+HYHoab6kqUDUVhKu/A/zqrLOh6Io\nHNwfRa0W2P3wzQ1GPqfwygtTuMpUN20Zu9CY508l6e3M0LZdT03DIjSAprWiDJEjxO17iX+AAt0f\nxPP6VlnKMcdjeQ69FMVZpiquEluEaDTK6dOnOX/+PLlcjqqqGoaHx8nnkzidbnbs2EZjYyOiOPv6\nUBSFaDTK2NgYAmrOnzDQ0mqmufX6dZdOp3n++eeZnJzkiSeeoKpq/ky8/F//EdJYAOWP/+eSerxM\nd68s6Y0lRwR9Pp8XqGO2ftRfAlsWMbdiBP1+/3+aHuPfgL8FXMBOCquNe1ntHV4Uo8bNGsfDdEy+\nxFrnY1i0FXRMHuD8+PdxSy4+nX+Gz+R8BCU3uvvUvPlKlONvJbj3QdNMS9ZcVuH4kTgTozk2btFT\n17TwjXSt8zH6I0c5o6vinmQ3+ql3SVp3LmregiDQ0KTl3KkkwYkcDtfCp+FQfyGV9mZzu9mYG+7S\nk0lLnD2RxGCScJWVdvobg69iiBwhYd1F3PHwkuewyvsTRVE4eyKJIMCmbYaSb7pms5n777+fbdu2\n0d7ezoULF/CUORHz6zEZvFRWWOYYCyicixaLBYvFQn93GlFI4q2cfS5qtVqeeOIJvve97/HCCy/w\n1FNP4fF4is5D3PMxDIkocVkGaWXVBkpaYfh8vj8BvgpMAqkb/uTx+/23JLjp8/kOU5AaSQMX/X7/\nc9Orij+l0Ee8EfidErOkPlIrDIB0LspPOn4Ti7aSvJImnOqn3NTGlvIvYMuZcXb3IubzRCrK6cmY\nOfZWgooaNVvuMWCxONj/fD+hYJ7N2w1U15emJflazx+TzIb4nGED2nQ/wZr/uOhsoVxW4dUXpnB7\nVWzdNf+qQZXoJtVxkMlUBZWb1hdqHm5BgsNstvMjfx/plMLuh0wzAcT5MIQOYZp8qXhDpA8AH9Tz\n+lZY7DH3d6dpP55k41Y9dWtuXX02Eio0GVNrBe7dZ1qwE9+xNwsCog9+wlLUUMViMZ577jkymQyf\n/vSncTqdRfdzK9/zYlYYpRqMy8Aev98/8p7X/9bv9//SUia5QnzkDAbApYkfc3b039GrHGwp/2kq\nzdtmTj4xm8PWP4AuGiNpMXMq6eb8+Sxr1mkJjiuEghm27jRQXlW68PDA1HHeHvhr7iv/Mm2hg+R0\nNYQrfnbR1c4X25N0X0mz7+OWeRtCGXv+AV22H0ksSCPIgpasvp6MoZGMfg15jWdR47pcLvp6R3nz\nlRgarcB9DxrRC5MIcgpBkQFlOgNMRp0awBR8hZRpE1OeZz5wxgI+2Of1UlnMMaeSMgf3T2GxFVSg\nl6ttb2gix9FDMQwGkZ37TGiLpJDncgov/yBCbUNBbmc+IpEIzz1XENX4zGc+U7Tg8HYZjFJdUmff\nayym+ddSJ7XKytHsfAyTugyvaSPq98hry2oVwYY6jOOTWIZHuEeVhFo35y+BpBLYcZ9x0bnjleat\nGNUurkTeotH1cSzjz0+7pu5Z1H7q1mjpvpKmtzPN+ra5WSmJiVHK8j2cmbgf79bd6LM9aBKdqJNd\nmCcKobOcxkPKtJmUua3kVY7RJHHfzhhTnSex9VzGpArNu23asI4pj+8DaSxWuTk9HWlyWWhbhCuq\nFOwuFTvuM/Lum3HePRRn6y4DBoM4S+VgfCSLnOemFeJWq5Unn3yS733vezz33HM8+uijC8Y0VpJS\nDcZln8/3AvAyhayla/wOsKq6docRBRXV1h3zbyAIxMtcZExG7H397NIN422yoWltRtIsvl2pKIg0\nOR7hzOi3CXieRWtowjTxIhlDE3l18SVzMQxGEW+Vmv6uDGs36GbiKlCQZsh0HEV2CTjW34OoNZHW\nbiRtKjS4EbNhtIlLaKPtmIIvYwq+TEZXR8q8mbRpA4qgRUAGJQ+KjICMkE/A4Ds4xo5SlhlD8QoE\npmoYUO3C2+BCEEUUxGnjIKIIKnLailVj8SElny/oknkqVCvSbtjlUbNtl5Hjb8V5/SdRBBEMBhGD\nScRoEomE8qjVAg73zW/DTqeTp556ihdffJHnn3+eHTt2sH379qIxkpWkVIPxy8AZ4L3lhKtaUh8g\nsgY942vXYB0apjEYQh7rYqTCA0s46Rrsezg//n2uBl/G5X0WR/9fYh59jnDlzy3qBtuwVsvwQJbB\n3syM/zg4keP4mxGeXneOpK4FnW3uykFW20had5K07kTMBtFF29FFz2AZ/wGM/2De8RQEZF0dUffj\npIytdF5Q0XkpzVa7gYrq1X5gHyUC/Vky6dm6ZMuNp0LNA4+aCU7kSMQLLZsTMZnQZIZcFmoaNCXX\nIrlcLj772c9y8OBB3n33XYaGhnj00UcxGpeWObgUSjUY3y4Wq/D5fH+6zPNZZYVRJIlwTRUZgx7b\nYABnKkmwvhZlkdkVaklPg+0BOoKvssnzDBrXJ7GMfRd9+AhJ++6S92N3StgcEt1X09Q2aghO5Hn3\ncIw1rk50qgRhx82bEslqBwnHXhL2Pagyw2gSnYByfbUgiChIIKgwVW0nPHVddr1lk0JgMEtvR3rV\nYHyEuKZLZrKIuDzLLx9zI2arNC2xM3v8bFZBvUARajE0Gg2PPPIIVVVVHDp0iO985zs88sgjt63W\npqRPaoHA9i3VYKxy50i4nJgsVjQXL+Hs6mWyoQ5FtTij0eR8hKvBA3QGX2FTmQ9t/AKm4AEyxrWF\nYHQJCIJAw1otp95JcPlcip6raXQGka0N58nnbWQMN+/LfMPOyGkrCm6keTBp7BTECq6PX9ug4dLZ\nFNGp/LL0SF9lfnThCLIkkTHf2bLH8GSeSCjPxi1zdcluB4IgoNEsbVxBENiwYQNer5f9+/fzgx/8\ngFAoxMaNG1fcRbWQvPn9fr//8PT/f3+ezf4v4BsrMK9VbgNyhZepRBx73wCurm4mG+uRVaU/bZk0\nZVRbttMRfJVm508x5X4SZ/9fYRn9LqGqr5Sc/lperUbXLtB5KY3ZInLf7gz6kU5ijoduS/ygul7D\n5fMp+rsybLhrtSf3SiHmctj7CkpA42sbyenv3Gfd05FGpYaqug/uqtLpdPLMM89w6NAhrly5woYN\nG1bcYCy099/2+XzXHgO+AtQX+VkV0/mAk7JZCdbXIqXSODu6ETOL6x62wf0pcnKay5MvoqjMRMue\nQJ0ewhB6Y+7GioKYDSPIs+XHRVFg3UYdLVU5Htwm4568hJBpRR1rwN7bj6OrB0d3L/aePuy9/dj6\nBrD1D2IeHoUFejaXilYnUl6pZqA3Qz53B/uDf8gxTAYRFAVZFHH09iPkV6Yj481IJWUCg1mq6zSo\n1NOpSlIAACAASURBVB/sxldqtZqHHnqIL3/5y6gW8bC3VOYdwe/3f/yGX//c7/fPUYz1+Xy/uSKz\nWuW2kraYCTbW4+juxdXZxWRjfdH+4sWw6qqosd5Dx+QBmp2PgWkjKVMbxuDr5NVOxHwSVWYEKTOK\nKjOKKKeQRQOhql8kr3EXdiLLtOWH0BrjMARgA2zoI0nyKhWKJBa0nBSm/y38SNksQj7PVNX8LqhS\nqW3UEBjIztxIhHweZ1cPCaeDhLMUVZpVFkRRME4ESZtMRD1unF09WAcDhGuqbnu3wr6uDIrMLSkH\nvN/QarVEo9Gbb3iLlBrDKCovPt/rq3zwyJiMTK5pwNHVg/tqJ6HaGtKW0oQBW92fYiDyDpcmfsxd\n3s8TdT+OOtmNdfTfAZBFHTmNl5SpjbzGjTH0BrbAPxOq+gqyZMbWP4g2FidSUY4sjWCe/D7his+Q\nMS2csW0ZCmAanyRjMpKyzd89rRScZSqMJpG+rjTVdRpMo+NoEknUyQBZvY6s4ZYEDT7y6MIRpGyW\ncFUFGbOJqLcMy8gYGZPxthpkOa/Q15XG7VUV7Ui5ysKs/BpmlQ8MWYOeibVrcPT04ejuJVruJVbm\nuukToFlbTq3tXrqCr9Hi/Cn0ajvhyp9Hyk6S03qRJcusfWR1ddiG/gFr4BvkpU9jCEeYKvcQL3Nh\nDbxAXq0mY5xfofMaU+VeNPEEtv5BxvW6kldFxRAEgdpGDRfbUyQnU3jHJ0hazKiTKey9/YyvbVp0\nUsAq1zFOTJLTaGYeQmKeMrSxBNbBABmDgZz+9ni3h4eypFMrm0r7YWa1ImmVWeS1GiaaGknZrFiG\nR7D3DSDkbx4n2OD+FLIic3HihcJ+NC4yxmZklXWOwcnpKomU/zSauAXTeIi4w0aszI2YDaFJdJCy\nbCstYC6KhOpqQBBw9PYvHM9QFKRUGhaQwqmq1yCKoO0fQQCmKisI1dUgZXPY+gcXfO8q86NOJNHG\nE8RdzuvngiAQqq1CliTstzGe0XM1jcEkFm2FusrNWTUYq8xBkURCtdVEKrzowhFcHV1I6YU75Jk0\nZdTbd9MdOkg8c3NNGzHrQUxvRZaGUFSHAQX91AkAkpbtJc81r9EQqq1CnUxhHRouuo0qlcLZ1YPn\n8lWk7t5596XVijRVK1QQJepwkNdqyBoNTJV70U9NYRz/aGkyLRfG8QlkUSThnF2AKavVhGqrUaXT\nWAcDK26Qw8Ecock8dWs0dySV9sPAqsFYpTiCQLzMTbChDimbxX21E00svuBb1rueABQuTa8y5kOd\nSGDv6yerNxCpMKJLnMc0/iN0UyfIGJqQ1XObNy1E2mIhWubGOBlEH7yuCyXk85gDw7gvd6BOpkgb\njUg9vejCkXn3tcUaJisLdGSuzyHudpK0WrAERlDHFy+l8lFGzGbRhyMkHPaixaHX4hmGUHjWd7cS\n9HZkkCSoKVGVeZW5rK7LVlmQtMXM+NpGHN192Hv7GG9uQlYXF0szalw02PbQFXyDXcoDWOIKebUK\nWVX4uZbxZAmMIEsqgg21yOo1iEoUY/hNAKKWx5c0z2i5B008gXVwiKxBjyqVxjoUQMrmiDvsRCu8\nyKKIt7cfW/8gE1rtHL+5JhbDko5xOm6jK5SnvHH6D4JAuLoKd7KjEM9oXoNyG1IYPwxcS6WNu+bX\nGCvEM+JYAyOkrNYViRVlEjlCQwmq6gyoNavPyUtl9ZNb5abktVpC9TUIslwovFrAdbDO/TiblM24\nxuMIiowqnUYXiWAaHcM2FMDeP4igyAQb62YMT9z5GEnLdrIaLxljy9ImKQiE6qpRRAnX1U4cvf3I\nKhXjTQ1EaqoKBYmiSK5tI4oo4ujpRcjd0PFXUbAERsirVSTLnIQm80yFr/vVFZVEqK4WKZfDfmM8\nQ1EQ8nnEbK7gtluGupAPDbKMcSJIymwir1sgyCwIRCrKEfN5TOPjyzq+NjKFrW+AqqtX+HzDMFtd\nU6uxqFtg9TFplZLI6XREKiuwDwxhGh0j5i0u/WFLa2jI76Nb6CJbezdmXXnhD4qCmMsh5nLIavXs\ninJBJFr2VOFCvgXf8jWfuHUwQNTlmB1kvYZWS7C+FldnN47efiYb60EQ0EWm0CSShKorqTDpuHAu\nQ19Xmo1br6fTZg16IhXl2IYCeM9fBFlBfM/NRxZFUlYLSZuVtNm0JGHHDwv6cAQplyPsvrnOUc6g\nJ2GzYhyfIO5yzruKvSmKgjAxia1vAF1kClGWkSWJnoQBtShTEx4nLuWJVFXc9vqPDwOrBmOVkkk6\n7GhjcczT+fMZ02w9ICmdwd7TT06r5oD8Mu6JADur/u/CHwWhYCgWuhEswwWcMZsYX7d2wW2yRgPh\n6krs/YNYhoaZqvBiCYyQ1WlJOuxoBIGKajWDvRlaNuqRZYV0SiGdkkknTbjULsxSDo1RhagSkSUR\nRRBBFFAnEujCUxhC4VnGI6/RIGUySNksqkwGKZNFymTIGAzLUnj4fsQ4MUlWqy0YzhKIlnvQhyOY\nR8eIVFUuaUzL0DDqiUkkSSRls5K0WRnL6Tn8SozWu3TYTWHMY+NI2Syh2ppCUegqJbNqMFYpHUEg\nUlWBJpHA3jdQiGdMrxSEvIyjpw9BUQjVN1IX2culiRdodj6GQ99whyc+l6TDjjqZxDQ+iSqdRpXJ\nMFlfO2O0ahu1DPZleen5YgHyggaSIBTUdt1eNW6PCqtdQnQ6iFQpaKMxdOEI+kjBeNyIIgjkNWoU\nQcA0MUnSYfvQFQaq4wk0iSThytKf5PNaLQmnA8NEkJjbTV67uOC0diqKaWKSfFUlow7bzOpu8HQS\nQYSKWg1RrZe8Ro11MICzq5tgfR2yevU2WCqrn9Qqi0KRJIK1Nbg7urD1DxKsrwXANjCIKpUi2FBH\nXqdlnfqTdIcOcXrkW+yr+8/vyzTGqYpy1Mk0umiMtMk4q7Ld7pJY36Yjl1PQaEW0OgGtVkSjK6iM\nRiN5xkdzjI/kuHI+xZXzoFYLVNaqWduqA4uZtMVMRCkYDyGfJ6/RkNdMu+MEASGfx3PxCuaRMYIN\ndbftuMOTOcZGcjSs1a6YlpJpOpU26VhcxlvUW4Y+GMI8Mkq4trrk9wm5Qq1MVqdFaWqEUCHjSpYV\nhvozeMrVM21SE9MuL1tvP66OLiYb626p6POjxKrBWGXR5Ax6piq8WIeGMY5PIMgK+nCESIV35qar\nlvRsLPs0J4a/wWD0BNWLqK24bQgCwbpqLIER4u+paBcEAVNVFyaNB6Nmrg9eqxNxedSs2wTptMzk\naI7RQJa+rgyDfRnWrtdR16RFkoR5JVYUSSJW5sIyPIo6kVjRVYaiKIwN5+i6nGJy/Howf+2GZa6w\nnk4e0IcjRD3uRfdZkdVq4m4nprEJYmXu0irAFQXbwBBiPs9kQx22G8acGM2RTilU1c12haasloIU\nTncvrqtdhOpq7rjk+geBVQfeKksi7rpem2AeGSVhtxF/T3Cz3v4AVm0V7SP/h7y8OBXc24WiUhGp\nqSKnm31jmkoP8Ubf19jf+VucH/s+ufco7N6IVitSUaPhrnuMPPCYGYdLxcX2FG/sjxIYyKAskJUT\ndznJSxLmkbFlO6YbKbQhTfPGS1GOvRknHpdZv1mH26sq9LNeTnVeRcHWP4hpfIK4y0F0nsSImxEr\nc6OIIpbhkZK214fC6CNTRL0ecobZkumDvRnUGqFo3/qs0cDE2kZklQpnVw+m0bHVDKqbsLrCWGVp\nCALh6krcySSySkW4unKOr1oUJDZ7n+VQ35/RETxAi+vj8+zs/Ud36BACEuXmzVwYf57u0CE2ez9L\nteWeOe61WGaMwakTBKKnUIt6Kjdup3rNRq6ehZNvJ7A7Jcqr1KTTCumkTOpaAD2lYLKI7G1y4poc\nQx1PkDUu3ypjYizHqy/0kkzksdhE7rrbQEWNGlEUsDtyHHk9Rn93hoa1t+6OEfIy9r5+dFNRprxl\nxDxlRWMX0ak8kiRgMM7/rKqoVMQ8bizDo2hicTKm+VuQSpkM1sEAaaOhoHt2A9mswvBQQX1Ykoq7\n3vJaLRNrG7EODBXGiycI1VQXrwVRFLRTUfThCDG3a45x+iiwajBWWTKKSsV481oUUZg3sOk1baTc\n1MbF8R9SZ9uNTmW5zbNcPHk5R2/4LSrMd3Fv9a8wHr/CqZH/zdHBv6PD8Cp3eX8GlahmYOo4g1Mn\nCKf6ALDpaolnJwkEziAg4m5uoSxzF6GO9VxstxR0qnQCWp2IwSRid4gEBjO8eFLDs/US5pFRgo31\ny3IMwYkcx96MYTKraduuw+VRzTJ0DrcKh1ui63KKukYN4jw3VABkGX04gqxSkTEa5riZhFwOZ3cv\n6kSScFUFiXmK9OS8wtGDMRQFdj9swmCc310Vd7kwjk9iHh5hck1D8fNLUbD1DQIQrqmes83wQAY5\nD9U3aZKkSBLh2moyRgPWwAjuqx2E6mrJThsEMZfDMBnCMDmJarpfjDYaZaKp8SMX+1g1GKvcEqWk\nJbZ5PsfLXb/HhfHn2Vr+xdswq1tjOHaadD5Kg/0BANzGZh5u+CN6woc5N+rnle7/d2Zbp34NbZ7P\nUWXZhklThqIohFK9DE4dZ3DqOGO5b0G9QIN1H9sqvzhnddK4Tsvxt+KcGDNxjxJBHYuTfc8T9bX4\nQ+elFMmkwsatejxFXCzXCE/mePdwDJ1O5LEnKkkkw0W3W7NOx7HDcQb7MtQ0FL/xaaIxrIMB1OmC\nS06hUI+SMRlJG43kNRrsff2o0hlCdTULysyPBApKsYIIxw7HufdBM+p52pQqkkjUU4ZtKIA2Gisa\nBzKOT6CNxwlVVxXNqBrszWA0idicJcRRBIGE20XWYMA+HQyPestQpdLowxEERSFtNDJVUU5Oq8XZ\n2Y2zq4eJpsal14x8AFk1GKusOFZdJY32vXQFX2eN/SGsuqXl2N8uukOH0KvseE0bZ14TBZFG+x6q\nLTvoDL6KWtRTZdmGXj1bUE8QBBz6ehz6ejaWPc1Ueogrk/vpDr9GmbmZWuvOWdubzBK7HzJz/rhA\nMhdFuTxMtq0RtVqYzvDJ0nUpRXRKRm8QkFQCxw7HaWzR0rJRhyjOvuFGQjneORxHoxHZudeEwagi\nkSx+nGVeFRabROflQg8Q4YZ9idkslsAIhlCYnEYzk3KsicfRxOIYxycxjRXEGGVRZLKh7qZB4/7u\nDDqDwObtBt49HOfk0Tg7dhvnHMM1Ek47pvFxHD195NVqZHVBXkZWqZAlCdP4BEmrpWgmViKeZ3I8\nT3OrblEZelmjgYnmNdj6BrAMj86IJsadzlkB+GBDHc6uHpxdvUw0NSwc3L8WF3kfZgouljtuMHw+\n31eBOmACaAK+TCHR/WtA9/Rrv+f3+0fv1BxXuXU2lD1FX+Qo7aPf4f7a92+jxkQ2yEjsLC2uTyIW\nkVjXSAbWu0vTuxIEAauuim0VP8tUOsDJwDdx6ZvmZF2p1AJtO00MX3DQkJvgpTfG0VdZ6OtMk0wo\nmK3X4w+KDBfOJOm6nGZyLMfWXYYZ1040kuedQ3EkFezca0RvWHj1JwgCTeu0nDyaYHgoS0W1BhQF\nw0QQy/AIgqIQ9ZQR9bhnahpmnvRlGU08gTqZJG023zSbKRHPMz6SY+0GLW6vmo1b9Zw9keTimSSt\nW+aJ24giwfo6DMFgQXoll0OVTiPG4ojTacqRIrEzgMG+guvovdlRpSCrVAQb6lAnEuR0uqLGIGs0\nEKqrwdHdi6Onj8mGujlV/UI+j3F8AtP4ZCEJoNy76Lm837ijWVI+n88L/C7wy36//w8AI/AU8F+A\nV/1+/9eAHwCrnf0+4OhUFta7H2c41s5I7Nydns689IbfREGhwX7/su1TFCTuqfpFFPIcG/oHFGWu\n3pQgCOjXeciKEhtNES6fTaE3iuzYbeSBR81UV0kYIhFMU2E2bdWzdZeBWDTPoZcLmVixaJ6jb8QQ\nBNi5Z+H4wI2UV6kxmkQ6L6Uhl8PV0YVtKEDWYGCsuYlouYdkCk6/G+fK+SSJ+PTcRZGM2US8xNTX\n/u6CPH51fcH1VduopWGtlp6ODD0d82eg5fQ6piorCNfVMLmmgfGWtYxuXM9wWytj69bOlpiZRlEU\nBnszON1SyZ/DHASBrNG44MohbTETrqlCG4vP0lgT8nlMo2N4Ll7BMjKGIgqYxiYQMwu3CCiKoqBO\nJDGOTWDv6cMyNHxHM7nu9AojAWQACxAGTMAFCquLP5ne5gjwL3dkdqssK02OR+gMvsbJ4X/lofrf\nR6sqrQXs7UJRZLpDhykzrMOkWVpK6HyYNB7u8v40xwP/xJXJ/UUzxhRJJOF1UxkY4ZHdIka7Gt1U\nGG3nFJp4gmvP0fpQGLG2GusjZk4dTXDy7QQqNYiiwK59pkW1HhVEgcYWLWdPJFF3j6BOJAnVVpO0\nFRpfBSdynDgSJ5tVkPNw9UIal0dFTYMGb6V63uyjWcclKwz0ZHB7VbOyo9a36YjH8lw4ncRoEoum\nvs4/8fnHnRhNE4/KrGlZ+SympMOOmMthDYwgDwbIazQYx8aR8nlSFjNRbxmySkXZpauYR8aI1FTd\ndJ9SOoM+HJlx/4nTgpZ5lQopMkXWoCdpX1xB5HIhLJQjfjvw+Xw/A/w0MAwIwC8Bk4DH7/eHfT6f\nCsgCar/fnyvy/p8Hfh7A7/dvzSzFigMqlYpcbs7uP9TciWMOhM/zo7O/h8vUwBNtX0Mt3Z7WnNdY\n6JgHQ+388Ozv8FDLV2n27Fv2sRVFYf+FP6YveJynt/wVLlMRyZR8HvWRo5DNIUxfm7LJhOJyIruc\nCPE40pUO0KjJbWwlZzJz6p1J+nri7HvMi8OlvTYYQjCIKjxFtq4GFnhSzucVXv3OVT7uCaBUV5Bv\nKbTH7bw8xZGDYxhNah76eDmSSqDz8hQdl6LEYzm0WpGGZjObttgxGOd/9hzojfPqT4bZ+5iXusbZ\ncY5sRuYn3x8kFs3x8acqsTtLyzpSFIV8TkGlnuskeffNCa5ciPDZn61Hc5ukzKWOTqS+AQBkp4N8\nQz2K9XpGoHSlA3FgkOzOu2Gh1OlMFvU7xxAyGRSjAdlmQ7HbkG020GpQnTiFEE+Q3bkDbsjQupVr\nWaPRAJQUYLmjBsPn820G/hXY4vf7cz6f78+BPPA5YJff7x/w+XwOoNPv95fSKV4JBAJLmovL5WJi\n4qPVUe1OHfPg1AneHvhrPKaN7K75NUTh9i10Fzrmdwb/nkD0NI83/w0qcWWa7KRzUV7q+l00kolH\nGv4Iqcg4unAEfThC2mwiZTYja2Y/easTCew9/Ui5HJGqChIO+/UnbkVBF45gHhtHnUwBkHDYCS/0\nZKso6M91oc+m6alqxOLWculciq7LaZxlKrbtMqDRXr/xKrLC+FiOge4Mw0NZrDaJex80zRu8PvZW\njNBEnocftxTdJpmQefOVKLmcQsNaLY3N2nl7ViiKQmAgy9ULKWJTMmariMOlwu5S4XBJ6PUir74Q\nxeWR2LJz/vqNZUdRMEyGyOp1RWtpxGyOsktXSFvMhbbC8+zD3luoZZloaiha+S+l0pRd6SBtNhVk\neaa/91u5lisqKqBEg3GnK70rgeANK4dhQMf/396dh8dVnYcf/97ZNZJmpNFol2XZ8m5ssA3YYIyx\ngUKIS0JJDmlCEtoU0qRZaJI2CQ/9hYYskJD1CUlDQ5KmTxZOISsk4JjNwRiDY4wXvGJZmyWNpJE0\n2kajWX5/3DFIsmSPdmv0fp5Hj3Vnrs49R3d8X50dngBODydZnzwWaaLMczFrSv6Rxq59vFz/38O2\n6QP09rezq/6H/On45+jtn9zd2CKxbupCL1PuvWzSggWA05bNpSV3EOqrZ1+THvaccI6XtopyevJ8\nZwQLgH63OZKnLyuTnNp6vLX1GNEY7pZWCg4dxVddC/EEbXNKiVWU4w62kdE2/NBaAFdHiNx4L6+2\neTl0OMorO7p543AfFQscrNuYOShYgNmMVVBkZ83lmaxe66Y9GOPowfDwZemNEzgVZc48x4gBJcNt\nYf3VWRQW2zn2eh9PP97JsdfDRPvf+mPWDBQRnn+qkz07zV0PFy5z4sqwUF8TYe+uHp55opOtvwvR\n1xen7BxzLyacYdDj94048TJut9Gdn0dGewf2EYatvTVjvWDEZWJiLieh4iJcoU4ygiPf08ky3X0Y\nTwI3JGsW7cAFwJ1AH3C/UmoRUAmcv8NqxJhU5l5FX7SD/YFHcdo8XFT43jeHP8YTUY4Ft3Ew8Gti\niQgGVl6s+x6bKj4/abWRmo6dxBL9b869mEzF2StZ4LuGo8GnKM6+cNDw3VSdHsmT3dhEdlMz7mAb\nBhBxZxAsKSfs9YBhkOnzEW1uwVtbT8SdceZEs3gcT30D/S4XfYV5NL/eh2HAitUZVCw8d/NQSbmD\nQGOUY6/34S+04y8YfH9qqyIkElA+/+wP8MwsK2suz2RBm7mY4+H9YU4c7WPhUicZmRaOHggT6oiT\nmW1h9WVuSsrsbw4DTsQTdIbiBFuiBFui2G1O/IUTv2vfeHUV5JPZEiS7ofGMCZqWQTPW88+aTnd+\nHq6OEN76U/RlZxJ3TF1wnNaAobWOYfZZDOf2qcyLmHpL/TcSjoY42vokLquXpflbCHQf4q8N/0Oo\nr56irJWsLrqVtnA1O+seZG/jr1hdfOuk5OVE23ZyXOXkuiomJf2hLix8D01dr/NCzbdZnn8Ti/3X\njz4YGgadxUVE3G4y2trpyfOZy2gM7BC2WGifO4f8I8fJPVlLy8L5g4Z/ZgWasfX301JeRoXTSVdX\nnPL5DvyFqXdAX7Aqg2BzlFdf6mbj9dlv9hskEglqTkTIK7Cl3BHvzbVx6YYsgi1RjuwPc3CvWXPJ\nzDKHFpeW2wfNFwGzxuPJseLJsVKxwHneNi8nrFY6C/PxnmocvORJImHu4sjwM9bPYBi0l5eRf+QY\nObX1U7rS8XTXMMQsZhgGq4reR1+sk32BR2js2keg5xCZdj9XzLmTkuzVGIZBtrOY1p7jHA0+hd9d\nSfmQyW/j1Raupi1cxaqi90/ZMuw2i5OrKj7LnoafsS/wCNUdL3JxyT/gdy8cdVp9Xg993pGXXIk5\nHLTPKcV3sgZPQxOhUnMXRGskQlZTM705XiLZWThgTO3+NrvB6svcvLCti32v9LLmcjeGYdASiNLT\nHWfxBaMf2ODz27hsUxYtgSj9kTiFJfYRm7Rmkm5/HlnNLXgaGmlJLnmS2dyKs6ub9jmlKe8BEnM6\nCJUUkVN3CndrEPLPXiuZKBIwxLQyDAuXltxBJNZFc/dhluffxBL/ljP6ES4seg/BcBUv1/8Ir3MO\nXte5hyeC+Vduf7yH3v42+mKd4ColHAWnNQvDMP8Srmp7HothZ6738gkv39m47T6uKL+TutBu9jT8\nL09X3Utl7mZWFr4bh9V8cMcTcUJ99bT2vkFrz3EgwcrCW0a9Jlc4x0u330dWc4u590dypWGAUMn4\nJ5Tl+GwsWeHi0L4wtVXmUiM1b5grxRbPGfvSGUObuGY8S3LJk7pTOEOdxJwOPA2NhD3Z5uCFUejJ\n8+HqCOE51Ui0fISO9AmWZndDzERWi40N5Z8hGu9980E5lMWwcXnZx9l64m521H6Ha+d/Ebt18Dj7\neCJOQ9de6kKv0BNppSfaRm9/kFhiwFDrk+Y/BlZcNi8Z9hxCffWUZa/BaZue/RDKPBdTmLmcA4HH\nOBbcSn3nbsq9l9ERrqW19w2icbNZxmHNIhrvo6n7IOvnfGLUOxl2lBTj6Oohp6aOUFkJGe0dhIoK\niE1QG3jlEifNjVEO7Okly2Olsb6fuZUjrxQ7W/Xk+cgKtOBpaCJhmEurDLfa8zklV4wuOHwM2+uH\nYW7ZpC8/Mu3zMCaYDKsdhZlY5ubuIzx78iuUZq/m8jmfwDAMevqDVLU9z4n25+npb8VpzSbLUYTb\n7iPDnkuGLRe3PRen1YMz00IgWEs42k5vtJ1wtJ1IrJs1xbfhy5iYlWLHI9hbxe5TP6E9XE2Oq5y8\njEry3AvIy1hAlqOQtvBJdtR+h3A0xJriD56zk37oPbaFw/iPHscSTxC12wksXXTGkhbj0dsT5/mn\nOonFzIl+G6/LxpMztR3QM+FzndHWbs4OB4LnWLTxnGm1BvFEYwTy80iM4V6OZlitBIykmfAhm2gz\ntcxHWv7E3qZfsMB3Db397Zzq3EOCOEWZK6j0baYk+6IRO5BnQpkTiQTxRAyrZfgy9EU72Vn3IE3d\nB6nM3cyqoluxWoZv9hmuvBnBNnJq6s65uuxYNdRF2L2jhxyflQ3XTv1s/plwj0kk8J04SdTlJFRa\nMu7kpmoehjRJiRlnUd71tPa+wfHgNpzWbBbnvY1K36YJX85juhiGgfUsI6actmyunPvvHAj8H4da\nHqctXM36OZ/AbU9lbqu5nEXY6xn19qmpKi5zsHodZHvPv6Gt5w3DmLC9T6aSBAwx4xiGwdrSO5if\nu5F895IR/7pOZxbDwsrCW/BlzGdX/UP8+cQXuGHB187o1xnJZAWL00rnTvHEOTElpnumtxBjYrU4\nKMpaMSuDxUBlnkvYUP5pwtF2akK7pjs7Is1JwBBihst3L8bjLKWq7flJu0Y8EZu0tMXMIQFDiBnO\nMAzm5VxJa+9xQn31E55+d6SF3x/5OIdb/jjhaYuZRQKGEGmgImc9Blaq2rZPeNqvt/zOnI3fpGnt\nPTHh6YuZQwKGEGnAZfNSkn0RJzt2EE9M3B4nXZEmqtq2M9e7ngx7Di/V/YD+2PAr04r0JwFDiDQx\nL/dKwtEOGjr3TViaBwO/xWJYubDwPawt/TBdkSb2Nv18wtIXM4sEDCHSRHHWhbhsXqraJ6ZZKtRX\nT3XHDhb4riXDnkNB5lKW+t/OibbnqAvtnpBriJlFAoYQacJiWKnwXsGpzr2Eox3jTu9A4DdYLY5B\n+48vz7+ZXFcFr5x6eNI3tRLnHwkYQqSReblXkiDGyfYd40qnPVxDbWgXi3zXDVoZ12qxsa7sFdZy\nnwAAEWdJREFUo8TiEXbVPzTibokiPUnAECKNeJwl5GUsoKp9O+NZJ+5A4DHsFjeL/TcMc41iVhW9\nj6buAxwNbh1PdsUMIwFDiDQzL3cjob56gr1vjOnnW3tPUN+5h8V5bxtxufn5uZsozV7NvqZHaA/X\njCe7YgaRgCFEmin3rMVqODgxxs7vA4HHcFizWJR33YjnGIbBxSUfwm7JYF+THmtWxQwjAUOINGO3\nZjDHeyk1HTuHnTORSMQJ9Z0iEus5473m7iM0du1jqX/LORcydNk8LMq7joau18Zdy+iKBOjsaxpX\nGukuFo8Qi0/cHJuxkNVqhUhD83I2crL9BU607CDPeiEA7eFaqtt3UN2xk95oEACXLQePs5hsRwke\nZzE1HS/hsnlZ4Lsmpess8F3DoZbHOdTyOJeVfXRMee2LdvJ01RcxsLJl0TexGLNrWfR4Ik5/rJtI\nrIdIvJv+WDe9/W109TfTHWmmKxKgu7+ZcLQdj7OUa+f/JzaLc1ryKgFDiDSU715MlqOA/fWPU+iu\npbr9RTr6ajGwUpS1guXZ7yQS6yYUOUVnX4NZG4mbNY5VRe9P+YHksGZSmbuZo61/YkXBu8hyFIw6\nr682/vzNYcD1ob8yx3vpqNOYaaLxMDvrvk9z92H6470jnGXgtvvItOdTnLUSu9XN0dYnea3pEdYU\nf2BK83uaBAwh0tDpBQn3Bx6lqfMweRkLWF38Qco9a3HaztwFL5FI0BcL0dPfSq6rYlTXWpx3PceC\nWznS8kfWlNw2qp891bmX6o4dLPPfSHXHTo4Ft6Z9wIjGI/yl5ls0dx9ifu4mXDYvDmsmdmsmDqsb\nhyUTly0Htz3vjF0XE4kEx4JPUZJ1EcXZK6c87xIwhEhTi/KuI89bTCZzz7kboWEYuGxeXLbRb9ma\nYc+lwnsFVe3bWV5wU8ppRGI97D71Y7zOMpbl34TDmsXepl/Q1nuS3IyKUedjJojF+3mx9jsEug+x\ntvTDVOSsH9XPryxUNHUf4OVTD3F95VeHDf6TSTq9hUhTNouL5SU3TMnWtUv8NxBLRDnamvq8jNca\nf0k42s4lpbdjtdiYl3slVsPBseCfx5yPUF89r9Y+Svw8nFAYT0TZWfd9Grr2cXHxP4w6WADYLA7W\nlX2ESKyL3ad+PK65NmMx7TUMpVQF8DRQm3zJA+wDPgXcB5wAFgJ3aa1lGIUQ56FsZzFlnos5HtyW\n0girxq79nGh/jiV5bycvYz5g9odU5Gygqn07KwtvGTTDPBV90U62Vz9Ad38Li3x1rCq+dczlmWjx\nRJxd9Q9R37mbVUW3UunbNOa0cl1zuaDgXexreoST7X9hXu6VE5jTszsfahidwIe11ldpra8C/gD8\nCPgKsE1rfR/wW+CB6cuiEOJclvq30B/v4Xjb02c9rz/Wyyunfky2o4jlBX836L2FvmuJJ/o50fbc\nqK4dT8R5qf4H9Ebbme9fz9HgUxwPnj0fUyWRiLP71MPUdOxkZcEtZ53fkqrFeTeQ717Mnsb/pSsS\nmIBcpmbaA4bWulVrvQ1AKeUELtZavwC8HdiZPG1H8lgIcZ7yZcynMHM5R1ufJBaPjHjevoCmp7+V\nS0pvx2ZxDHrP6yqlMPMCjgefHtW+Hq83/4bGrv2sKrqV65Z9nuKsi9jT8DMau/aPuTwT5dXGn5v9\nO/k3sTR/y4SkaTEsrC39ZwwMdtX/cMq20J32Jqkh3gv8Mvl9AWbtAyAE5CqlbFrrQZ8ipdQdwB0A\nWmv8fv+YLmyz2cb8szOVlDn9TXV511rfx+/33UVLdC/LS85ch6q+fR/Hg9tYWfoOlpZfPmwaFxvv\n4okD9xDiGAv8G855zZOtL3Ow+bcsKbyGtQsVdrudLRf+B7/e+2l21j3Izau+iS+zfNxlG4um0BGO\nBbeyovRGNlTejmEYE5a2Hz8brR9j2+Gvs7f+MVaXqQlLeyTnW8B4N/CO5PcBIBtox+zXaBsaLAC0\n1g8BDyUPEy0tLWO6sN/vZ6w/O1NJmdPfVJfXlSjDlzGf3dWPkG+/mEQiSkvPMZq6D9LUfZC23ioy\n7QUs9GwZMV+ZiXlkOQr468lHyTGWnvV6XZEAW9+4nxzXXJb7/p7W1lb8fj+h9h4uK/kk26ru4fev\n/QfXzr9nykcUAfzl5I9wWrNZmL2F1tbWCU/fZ1nBHM9a9tb8lmL75ditrlGnUVJSkvK5094kdZpS\nahPwota6P/nSE8Blye/XJ4+FEOcxwzBY6t9CVyTAthNf4DeH/5nnqu/jcMsfsRg2luW/k00Vn8Nm\nGfnBZhgWFviupaXnKMHekyOeF41H2FH7XQDWz/nEGc1bmQ4/V8y5k95oGy/UfptYvH+4ZCZNoPsQ\nTd0HWOr/23MOAhgrwzBYU3wbas13xxQsRut8qmHcAXx8wPFdwP1KqUVAJfCZacmVEGJUSrPXkO9e\nTCTWTWXuZgqzLiDfvXhUD815OVdyIPAox4JbWVt6xxnvJxIJ/trwE9rD1Wwo//SIM8zz3AtYW3oH\nO+seZFf9D1ngu5psRxEuW86ENg8Nl7/9gUfJsOVS6bt60q4D4LRlkeX0E+6c/JrkeRMwtNZ/P+Q4\nCNw+TdkRQoyRYVjYPO/ucaXhsLqpyNnAibbnuLDwljcnA3ZHmmnqfp2GrteoC73C8vx3UpJ90VnT\nKveuoysSYH/g/6gN7QLAajjIchSS7SzC6yxjcd7bUgposXiEN9qepcxzCW67b8TzGrv209JzlDXF\nHzyj5jOTnTcBQwghBlrou5bjwW282vhzbIaTpu7X6e43h5A6rR4W+v6GZfk3pZTWsvwbmeu9nM5I\nA52RJrr6GumKNNERrqMutJuGrte4svwzZ+3n6I/18kLttwh0H+J48Bmunnf3iMus7A88Sqbdz7yc\nq8ZU9vOVBAwhxHnJ4yyhKGslNR07sVvcFGQuYVHedRRmLsPjLB11k1Kmw0+mw08RKwa9Xh/aw4t1\n3+OZk19m49x/H7bm0BftZHvNA7T1nmSpfwtHWp9ie803hu2Pqe/cTVu4iktLbj9jLaiZLr1KI4RI\nK+tKP0JPfwteVzkWY3LG6JR6VrNx7r/xl5pv8nTVvVw197NkO4vefL+nP8jz1V+jKxJgffknKc1e\njS+jkhdrv8uLtd/jivI7sRjmozSeiLM/8BjZjmLmjmHpj/PdeTNKSgghhnLassjNqJi0YHFaQeZS\nNlXcRSzex9NV99LWWw1AZ18TT1fdS09/Kxvn/hul2asBKPNczJri22joeo1X6h8mkVy7qqZjJ6G+\nei4ouDkt9/WQgCGEEIAvYx6b592N1WLn2ZNf5o3gszxz8l6i8TCbKj5PQebgOSGVvs1ckH8zJzte\nYF/TI8QTUQ42/5ocVzlzPJdMUykmlwQMIYRI8jhL2FxxNy5bDrsbfoyBlavn3Y0vuUDiUMvy38GC\n3Ks53PpHtlc/QFckwAUFN2NMco1oukgfhhBCDJDp8LN53t0cbX2KytxNZDpGXlrFMAxWFX+AcCxE\nXegVfBmVlGStmsLcTi0JGEIIMYTL5mFl4btTOtdiWFhX+hEOOoop966b1AmB000ChhBCjJPVYk85\nwMxk6dnQJoQQYsJJwBBCCJESCRhCCCFSIgFDCCFESiRgCCGESIkEDCGEECmRgCGEECIlEjCEEEKk\nxEgkEtOdh4mUVoURQogpktL09HSrYRhj/VJK/XU8Pz8Tv6TM6f8128orZR7zV0rSLWAIIYSYJBIw\nhBBCpEQCxlsemu4MTAMpc/qbbeUFKfOkSbdObyGEEJNEahhCCCFSMuv3w1BKXQP8HRAAElrr/5zm\nLE0KpVQR8CXgQq31JcnXXMADQD2wELhPa310+nI5cZRSlZjl3QOUAa1a6y8qpXzAfcAJzDLfpbVu\nmr6cThyllAX4A7ALcACVwD8CGaRpmQGUUhmYZd6qtf5MOn+uT1NKvQSEk4cxrfXVU/HZntU1DKWU\nG/gv4F+11vcAK5VSV09vribNFcDvGDyE7k6gRmv9VeBbwMPTkbFJ4gN+pbX+utb6k8B7lFJrgK8A\n27TW9wG/xXywpJOdWusvaq3vBtyYfwyle5m/BLw64DidP9enPam1vir5dfqZNen3eVYHDOAyoFpr\n3Zc83gG8fRrzM2m01o8CnUNefjuwM/n+fuBCpZRnqvM2GbTWr2itfzfgJQvQzYAyk2b3W2sd11p/\nCUApZcOsWR0hjcuslHo/ZpmqBryctp/rAVYopT6rlLpHKXX6fk76fZ7tAaOAwQ/RUPK12WJWlF8p\ndRPwlNb6MIPLHAJykw/XtKGUug54HHhca72bNC2zUmoZsFRr/eshb82Gz/X9Wuv7gXuBu5RSVzIF\n93m2B4wAkD3g2JN8bbZI+/IrpTYBm4B/Tb40sMweoE1rHZ2OvE0WrfVTWuvrgXlKqY+SvmW+CQgr\npT6H2eR6qVLqTmbB51pr/XLy3xjwF8zP+KTf59keMHYCc5VSzuTxeuCJaczPVHsCs1kOpdQK4DWt\ndWh6szRxklX164BPAkVKqcsYUGbS7H4rpZYNaJ4As5lmPmlaZq31l5P9NfcBLwAva62/Tfp/rpco\npT404KWFwHGm4D7P+nkYSqlrgXcBzUB/Go+S2gh8ALge+AHwjeRbDwANwALgK+kymiTZwf08sDv5\nUibwIPB74H6gGnMU0efSZcRQcmTY1zFHhtmBpcAngAhpWmYApdTNwL9gjgx7kLc6fNPucw2glCrB\nLOcezJqEHfgUkMMk3+dZHzCEEEKkZrY3SQkhhEiRBAwhhBApkYAhhBAiJRIwhBBCpEQChhBCiJTM\n+NmeQoxHcqG6Y8BirXXPdOdHiPOZ1DDErKKUek4pddvpY611GFgxncFiaJ6EOF9JwBCznta6fbrz\nIMRMIBP3xKyhlPoq8BGgMfn1deC9wM2YM+BfBLYCG4GPAX+LOWP2Q8AlmEuFW4AbtdbNyTTXYC6h\nnQCiwL8kFzkcem038FOgELBiLmPxqeHypLV+IrmA4D1AH+aCch/WWp9SSn0/meeHMWdyFwMHku/3\nKKWWAN9PXtYOPKy1/ul4f3dCgNQwxCyitf48sBdzQ52rtNZPaK3fh/mgRmsd0VpflTzdmVzA70Hg\n58AOrfV6zCVkPgSglPICTwL3aK03At8EfpfcyGio2zA3cdqIGZA2jJQnpdQ84FHgtmR+ngR+ljz/\no8nz1wLvANYAfuDu5HW+CPxQa70ZeDdwy/h+a0K8RQKGEMP7c/LfA4Bba/1S8ngf5oJ+AFuALq31\nMwBa6yeAIsyH+VBBYINSal1yhdGNZ7n2e4HdWusjyeNfAFcrpYoHnPOY1rpfax1Pvv+eAdd5l1Kq\nQmvdiFl7EmJCyCgpIYZ3el+BKIP3VohiLnIH5gZFPqXUcwPebwbyhiamtf5Vcm+Cbyul8jBrIz8Y\n4dplwLIh6VZjNmc1JI/bBrzXitk0BeYy7p8GnlFKnQL+H/DMCNcRYlSkhiHE2NUCdQO2yrwKWI3Z\nDzKIUsoPPKK1Xgco4EvJvTpGSnf3kHRXAfsHnOMb8L2ftwJJTnLXvUrgh8AflFKZYy6hEANIwBCz\nTSfgVkotVEp9fZxpPQ7kKaUuAUg+mJ8FvMOc+zHe2jJzP2bTkXWEPP0SWKuUmptMtwBzqfaB/19v\nVErZk/0l7wN+lXz9J0qpQq11AtiO2fEtI1vEhJBRUmJWSW7Xeh/QAXwW+CfMdv7DmJ3ZXwWuBXYB\nHwQeAZYA/4O5Ic13ARfwNa31N5OjpL4BGMmvr2mtHx/muuuALyfP8QB/TnZ4n5EnrfWzSqm/Ab4A\n9ANx4K7T/SjJpqodwEpgDmY/yx3JUVIfBO7AHF3lwRx19ciE/PLErCcBQ4gZJhkwfirDZcVUkyYp\nIYQQKZGAIcQMkpy4dxHwuSH7dwsx6aRJSgghREqkhiGEECIlEjCEEEKkRAKGEEKIlEjAEEIIkRIJ\nGEIIIVIiAUMIIURK/j8ul9rTyiZUAgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c0f66cf60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(paths[:, :10])\n",
    "plt.grid(True)\n",
    "plt.xlabel('time steps')\n",
    "plt.ylabel('index level')\n",
    "# tag: normal_sim_1\n",
    "# title: 10 simulated paths of geometric Brownian motion"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "uuid": "c9a7ad7d-921d-4b03-a81e-bff7d6e60b8e"
   },
   "outputs": [],
   "source": [
    "log_returns = np.log(paths[1:] / paths[0:-1]) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "uuid": "4fe20e49-2c58-454c-a086-14c2f2901dba"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 100.    ,   97.821 ,   98.5573,  106.1546,  105.899 ,   99.8363,\n",
       "        100.0145,  102.6589,  105.6643,  107.1107,  108.7943,  108.2449,\n",
       "        106.4105,  101.0575,  102.0197,  102.6052,  109.6419,  109.5725,\n",
       "        112.9766,  113.0225,  112.5476,  114.5585,  109.942 ,  112.6271,\n",
       "        112.7502,  116.3453,  115.0443,  113.9586,  115.8831,  117.3705,\n",
       "        117.9185,  110.5539,  109.9687,  104.9957,  108.0679,  105.7822,\n",
       "        105.1585,  104.3304,  108.4387,  105.5963,  108.866 ,  108.3284,\n",
       "        107.0077,  106.0034,  104.3964,  101.0637,   98.3776,   97.135 ,\n",
       "         95.4254,   96.4271,   96.3386])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "paths[:, 0].round(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "uuid": "cd6ee063-9463-405d-96bd-2ad1231d7e7f"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.022 ,  0.0075,  0.0743, -0.0024, -0.059 ,  0.0018,  0.0261,\n",
       "        0.0289,  0.0136,  0.0156, -0.0051, -0.0171, -0.0516,  0.0095,\n",
       "        0.0057,  0.0663, -0.0006,  0.0306,  0.0004, -0.0042,  0.0177,\n",
       "       -0.0411,  0.0241,  0.0011,  0.0314, -0.0112, -0.0095,  0.0167,\n",
       "        0.0128,  0.0047, -0.0645, -0.0053, -0.0463,  0.0288, -0.0214,\n",
       "       -0.0059, -0.0079,  0.0386, -0.0266,  0.0305, -0.0049, -0.0123,\n",
       "       -0.0094, -0.0153, -0.0324, -0.0269, -0.0127, -0.0178,  0.0104,\n",
       "       -0.0009])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "log_returns[:, 0].round(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "uuid": "77290ae6-4035-42a6-8312-ec89da50f88b"
   },
   "outputs": [],
   "source": [
    "def print_statistics(array):\n",
    "    ''' Prints selected statistics.\n",
    "    \n",
    "    Parameters\n",
    "    ==========\n",
    "    array: ndarray\n",
    "        object to generate statistics on\n",
    "    '''\n",
    "    sta = scs.describe(array)\n",
    "    print(\"%14s %15s\" % ('statistic', 'value'))\n",
    "    print(30 * \"-\")\n",
    "    print(\"%14s %15.5f\" % ('size', sta[0]))\n",
    "    print(\"%14s %15.5f\" % ('min', sta[1][0]))\n",
    "    print(\"%14s %15.5f\" % ('max', sta[1][1]))\n",
    "    print(\"%14s %15.5f\" % ('mean', sta[2]))\n",
    "    print(\"%14s %15.5f\" % ('std', np.sqrt(sta[3])))\n",
    "    print(\"%14s %15.5f\" % ('skew', sta[4]))\n",
    "    print(\"%14s %15.5f\" % ('kurtosis', sta[5]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "uuid": "57ac0ad6-14c7-4158-b67b-b553d662dc21"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     statistic           value\n",
      "------------------------------\n",
      "          size  12500000.00000\n",
      "           min        -0.15664\n",
      "           max         0.15371\n",
      "          mean         0.00060\n",
      "           std         0.02828\n",
      "          skew         0.00055\n",
      "      kurtosis         0.00085\n"
     ]
    }
   ],
   "source": [
    "print_statistics(log_returns.flatten())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "uuid": "1bb98c2c-002b-4e19-88af-ae23db1a673f"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1c3c05d6a0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYUAAAEMCAYAAAArnKpYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c0f66c978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(log_returns.flatten(), bins=70, normed=True, label='frequency')\n",
    "plt.grid(True)\n",
    "plt.xlabel('log-return')\n",
    "plt.ylabel('frequency')\n",
    "x = np.linspace(plt.axis()[0], plt.axis()[1])\n",
    "plt.plot(x, scs.norm.pdf(x, loc=r / M, scale=sigma / np.sqrt(M)),\n",
    "         'r', lw=2.0, label='pdf')\n",
    "plt.legend()\n",
    "# tag: normal_sim_2\n",
    "# title: Histogram of log-returns and normal density function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "uuid": "75c069e5-c518-4fca-8b60-de465ba1a56b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'sample quantiles')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZcAAAEMCAYAAAAIx/uNAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c1e2cf198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sm.qqplot(log_returns.flatten()[::500], line='s')\n",
    "plt.grid(True)\n",
    "plt.xlabel('theoretical quantiles')\n",
    "plt.ylabel('sample quantiles')\n",
    "# tag: sim_val_qq_1\n",
    "# title: Quantile-quantile plot for log returns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "uuid": "a6e5cdd2-0e90-4b34-8c13-d52dfe7e897b"
   },
   "outputs": [],
   "source": [
    "def normality_tests(arr):\n",
    "    ''' Tests for normality distribution of given data set.\n",
    "    \n",
    "    Parameters\n",
    "    ==========\n",
    "    array: ndarray\n",
    "        object to generate statistics on\n",
    "    '''\n",
    "    print(\"Skew of data set  %14.3f\" % scs.skew(arr))\n",
    "    print(\"Skew test p-value %14.3f\" % scs.skewtest(arr)[1])\n",
    "    print(\"Kurt of data set  %14.3f\" % scs.kurtosis(arr))\n",
    "    print(\"Kurt test p-value %14.3f\" % scs.kurtosistest(arr)[1])\n",
    "    print(\"Norm test p-value %14.3f\" % scs.normaltest(arr)[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "uuid": "d35f18c9-d798-47f7-85d4-dc09b0907134"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skew of data set           0.001\n",
      "Skew test p-value          0.430\n",
      "Kurt of data set           0.001\n",
      "Kurt test p-value          0.541\n",
      "Norm test p-value          0.607\n"
     ]
    }
   ],
   "source": [
    "normality_tests(log_returns.flatten())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "uuid": "80629df6-776e-4849-872b-46b6b35d4eb0"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'log data')"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAkAAAAEZCAYAAAB/85qUAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nFI4CIBERESkcBUAiIiJSOP8fxatctmCYg7gAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10944f6a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, (ax1, ax2) = plt.subplots(1, 2, figsize=(9, 4))\n",
    "ax1.hist(paths[-1], bins=30)\n",
    "ax1.grid(True)\n",
    "ax1.set_xlabel('index level')\n",
    "ax1.set_ylabel('frequency')\n",
    "ax1.set_title('regular data')\n",
    "ax2.hist(np.log(paths[-1]), bins=30)\n",
    "ax2.grid(True)\n",
    "ax2.set_xlabel('log index level')\n",
    "ax2.set_title('log data')\n",
    "# tag: normal_sim_3\n",
    "# title: Histogram of simulated end-of-period index levels\n",
    "# size: 90"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "uuid": "9e7b6096-9d21-4199-882b-b38f760fc72e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     statistic           value\n",
      "------------------------------\n",
      "          size    250000.00000\n",
      "           min        42.74870\n",
      "           max       233.58435\n",
      "          mean       105.12645\n",
      "           std        21.23174\n",
      "          skew         0.61116\n",
      "      kurtosis         0.65182\n"
     ]
    }
   ],
   "source": [
    "print_statistics(paths[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "uuid": "b9b2eab0-7788-48f7-b4b2-c3f1e263f0b6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "     statistic           value\n",
      "------------------------------\n",
      "          size    250000.00000\n",
      "           min         3.75534\n",
      "           max         5.45354\n",
      "          mean         4.63517\n",
      "           std         0.19998\n",
      "          skew        -0.00092\n",
      "      kurtosis        -0.00327\n"
     ]
    }
   ],
   "source": [
    "print_statistics(np.log(paths[-1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "uuid": "7bd3a6dc-ca9f-4878-bf30-27127547b952"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skew of data set          -0.001\n",
      "Skew test p-value          0.851\n",
      "Kurt of data set          -0.003\n",
      "Kurt test p-value          0.744\n",
      "Norm test p-value          0.931\n"
     ]
    }
   ],
   "source": [
    "normality_tests(np.log(paths[-1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "uuid": "fbe45821-3fda-4924-9b65-b7aae6004ae6"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1093efbe0>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY8AAAEMCAYAAAA8vjqRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n/h/LQGJ1uHHtQAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c15840eb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "log_data = np.log(paths[-1])\n",
    "plt.hist(log_data, bins=70, normed=True, label='observed')\n",
    "plt.grid(True)\n",
    "plt.xlabel('index levels')\n",
    "plt.ylabel('frequency')\n",
    "x = np.linspace(plt.axis()[0], plt.axis()[1])\n",
    "plt.plot(x, scs.norm.pdf(x, log_data.mean(), log_data.std()),\n",
    "         'r', lw=2.0, label='pdf')\n",
    "plt.legend()\n",
    "# tag: normal_sim_4\n",
    "# title: Histogram of log index levels and normal density function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "uuid": "1db3cb57-4537-4e8c-96ca-9a96cb35bf99"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'sample quantiles')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAY8AAAEMCAYAAAA8vjqRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nY4wxUft//uUrsUnAXhgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1094313c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sm.qqplot(log_data, line='s')\n",
    "plt.grid(True)\n",
    "plt.xlabel('theoretical quantiles')\n",
    "plt.ylabel('sample quantiles')\n",
    "# tag: sim_val_qq_2\n",
    "# title: Quantile-quantile plot for log index levels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Real World Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "uuid": "2fac84d1-67fd-4345-a9b8-58e8e20b6ea6"
   },
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "raw = pd.read_csv('source/tr_eikon_eod_data.csv',\n",
    "                 index_col=0, parse_dates=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "uuid": "8c2cddba-d3fc-4e22-8b22-b0a6dcf61f16"
   },
   "outputs": [],
   "source": [
    "symbols = ['SPY', 'GLD', 'AAPL.O', 'MSFT.O']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "uuid": "eaa5651f-3c91-4f0f-9941-b564e4b7dbe1"
   },
   "outputs": [],
   "source": [
    "data = raw[symbols]\n",
    "data = data.dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "uuid": "e4574de5-c00f-4665-b341-dad771d24d8e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 1972 entries, 2010-01-04 to 2017-10-31\n",
      "Data columns (total 4 columns):\n",
      "SPY       1972 non-null float64\n",
      "GLD       1972 non-null float64\n",
      "AAPL.O    1972 non-null float64\n",
      "MSFT.O    1972 non-null float64\n",
      "dtypes: float64(4)\n",
      "memory usage: 77.0 KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "uuid": "f2acb16d-fd16-4008-95a7-5213e3df3a9e"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SPY</th>\n",
       "      <th>GLD</th>\n",
       "      <th>AAPL.O</th>\n",
       "      <th>MSFT.O</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>113.33</td>\n",
       "      <td>109.80</td>\n",
       "      <td>30.572827</td>\n",
       "      <td>30.950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>113.63</td>\n",
       "      <td>109.70</td>\n",
       "      <td>30.625684</td>\n",
       "      <td>30.960</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-06</th>\n",
       "      <td>113.71</td>\n",
       "      <td>111.51</td>\n",
       "      <td>30.138541</td>\n",
       "      <td>30.770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-07</th>\n",
       "      <td>114.19</td>\n",
       "      <td>110.82</td>\n",
       "      <td>30.082827</td>\n",
       "      <td>30.452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-08</th>\n",
       "      <td>114.57</td>\n",
       "      <td>111.37</td>\n",
       "      <td>30.282827</td>\n",
       "      <td>30.660</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               SPY     GLD     AAPL.O  MSFT.O\n",
       "Date                                         \n",
       "2010-01-04  113.33  109.80  30.572827  30.950\n",
       "2010-01-05  113.63  109.70  30.625684  30.960\n",
       "2010-01-06  113.71  111.51  30.138541  30.770\n",
       "2010-01-07  114.19  110.82  30.082827  30.452\n",
       "2010-01-08  114.57  111.37  30.282827  30.660"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "uuid": "d4cf7b80-4be5-48d6-b669-acf6c9784941"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/yves/miniconda3/envs/py4fi/lib/python3.6/site-packages/ipykernel_launcher.py:1: DeprecationWarning: \n",
      ".ix is deprecated. Please use\n",
      ".loc for label based indexing or\n",
      ".iloc for positional indexing\n",
      "\n",
      "See the documentation here:\n",
      "http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1c1feab4e0>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeoAAAFkCAYAAADv13iSAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nREQkYErUIiIiAVOiFhERCdj/A3XopHxhg0x5AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c3cd1d198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "(data / data.ix[0] * 100).plot(figsize=(8, 6), grid=True)\n",
    "# tag: real_returns_1\n",
    "# title: Evolution of stock and index levels over time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "uuid": "8caf3129-34cb-4ce0-a53b-bef84d3db2dc"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SPY</th>\n",
       "      <th>GLD</th>\n",
       "      <th>AAPL.O</th>\n",
       "      <th>MSFT.O</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>0.002644</td>\n",
       "      <td>-0.000911</td>\n",
       "      <td>0.001727</td>\n",
       "      <td>0.000323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-06</th>\n",
       "      <td>0.000704</td>\n",
       "      <td>0.016365</td>\n",
       "      <td>-0.016034</td>\n",
       "      <td>-0.006156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-07</th>\n",
       "      <td>0.004212</td>\n",
       "      <td>-0.006207</td>\n",
       "      <td>-0.001850</td>\n",
       "      <td>-0.010389</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-08</th>\n",
       "      <td>0.003322</td>\n",
       "      <td>0.004951</td>\n",
       "      <td>0.006626</td>\n",
       "      <td>0.006807</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 SPY       GLD    AAPL.O    MSFT.O\n",
       "Date                                              \n",
       "2010-01-04       NaN       NaN       NaN       NaN\n",
       "2010-01-05  0.002644 -0.000911  0.001727  0.000323\n",
       "2010-01-06  0.000704  0.016365 -0.016034 -0.006156\n",
       "2010-01-07  0.004212 -0.006207 -0.001850 -0.010389\n",
       "2010-01-08  0.003322  0.004951  0.006626  0.006807"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "log_returns = np.log(data / data.shift(1))\n",
    "log_returns.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "uuid": "f6fefbe1-3ec6-4d1b-b774-9db3f3c38c83"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x1c1ff604a8>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x1c1ff70748>],\n",
       "       [<matplotlib.axes._subplots.AxesSubplot object at 0x1c200c2828>,\n",
       "        <matplotlib.axes._subplots.AxesSubplot object at 0x1c200fae48>]], dtype=object)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiYAAAF1CAYAAADcPCGCAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nMZEkScUwMZEkScUwMZEkScX4/wFESBqPaWF7ywAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c1e2be1d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "log_returns.hist(bins=50, figsize=(9, 6))\n",
    "# tag: real_returns_2\n",
    "# title: Histogram of respective log-returns\n",
    "# size: 90"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "uuid": "5e6f48e5-68f2-44ec-ad92-635ad3c249ec"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Results for symbol SPY\n",
      "------------------------------\n",
      "     statistic           value\n",
      "------------------------------\n",
      "          size      1971.00000\n",
      "           min        -0.06734\n",
      "           max         0.04545\n",
      "          mean         0.00042\n",
      "           std         0.00934\n",
      "          skew        -0.46886\n",
      "      kurtosis         4.54265\n",
      "\n",
      "Results for symbol GLD\n",
      "------------------------------\n",
      "     statistic           value\n",
      "------------------------------\n",
      "          size      1971.00000\n",
      "           min        -0.09191\n",
      "           max         0.04795\n",
      "          mean         0.00005\n",
      "           std         0.01048\n",
      "          skew        -0.60078\n",
      "      kurtosis         5.42113\n",
      "\n",
      "Results for symbol AAPL.O\n",
      "------------------------------\n",
      "     statistic           value\n",
      "------------------------------\n",
      "          size      1971.00000\n",
      "           min        -0.13187\n",
      "           max         0.08502\n",
      "          mean         0.00087\n",
      "           std         0.01605\n",
      "          skew        -0.26179\n",
      "      kurtosis         4.92237\n",
      "\n",
      "Results for symbol MSFT.O\n",
      "------------------------------\n",
      "     statistic           value\n",
      "------------------------------\n",
      "          size      1971.00000\n",
      "           min        -0.12103\n",
      "           max         0.09941\n",
      "          mean         0.00050\n",
      "           std         0.01412\n",
      "          skew        -0.10110\n",
      "      kurtosis         7.70109\n"
     ]
    }
   ],
   "source": [
    "for sym in symbols:\n",
    "    print(\"\\nResults for symbol %s\" % sym)\n",
    "    print(30 * \"-\")\n",
    "    log_data = np.array(log_returns[sym].dropna())\n",
    "    print_statistics(log_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "uuid": "83fc3d8b-03c4-43bc-a7a3-b7ac0747c2b1"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'sample quantiles')"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZcAAAEMCAYAAAAIx/uNAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nEYmdwkVERGKncBERkdgpXEREJHb/HxJ+jpQCHFWMAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c201ade10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sm.qqplot(log_returns['SPY'].dropna(), line='s')\n",
    "plt.grid(True)\n",
    "plt.xlabel('theoretical quantiles')\n",
    "plt.ylabel('sample quantiles')\n",
    "# tag: real_val_qq_1\n",
    "# title: Quantile-quantile plot for S&P 500 log returns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "uuid": "a6e1cee5-aebc-4c63-8ce4-100562f31859"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'sample quantiles')"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAZcAAAEMCAYAAAAIx/uNAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c20390fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sm.qqplot(log_returns['MSFT.O'].dropna(), line='s')\n",
    "plt.grid(True)\n",
    "plt.xlabel('theoretical quantiles')\n",
    "plt.ylabel('sample quantiles')\n",
    "# tag: real_val_qq_2\n",
    "# title: Quantile-quantile plot for Microsoft log returns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "uuid": "bce2aa32-77f9-4d5a-9a81-1a37b6b90001"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Results for symbol SPY\n",
      "--------------------------------\n",
      "Skew of data set          -0.469\n",
      "Skew test p-value          0.000\n",
      "Kurt of data set           4.543\n",
      "Kurt test p-value          0.000\n",
      "Norm test p-value          0.000\n",
      "\n",
      "Results for symbol GLD\n",
      "--------------------------------\n",
      "Skew of data set          -0.601\n",
      "Skew test p-value          0.000\n",
      "Kurt of data set           5.421\n",
      "Kurt test p-value          0.000\n",
      "Norm test p-value          0.000\n",
      "\n",
      "Results for symbol AAPL.O\n",
      "--------------------------------\n",
      "Skew of data set          -0.262\n",
      "Skew test p-value          0.000\n",
      "Kurt of data set           4.922\n",
      "Kurt test p-value          0.000\n",
      "Norm test p-value          0.000\n",
      "\n",
      "Results for symbol MSFT.O\n",
      "--------------------------------\n",
      "Skew of data set          -0.101\n",
      "Skew test p-value          0.067\n",
      "Kurt of data set           7.701\n",
      "Kurt test p-value          0.000\n",
      "Norm test p-value          0.000\n"
     ]
    }
   ],
   "source": [
    "for sym in symbols:\n",
    "    print(\"\\nResults for symbol %s\" % sym)\n",
    "    print(32 * \"-\")\n",
    "    log_data = np.array(log_returns[sym].dropna())\n",
    "    normality_tests(log_data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Portfolio Optimization"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "uuid": "74a583b1-1e85-4efa-adf0-c70377606aa6"
   },
   "outputs": [],
   "source": [
    "symbols = ['AAPL.O', 'MSFT.O', 'AMZN.O', 'GDX', 'GLD']\n",
    "noa = len(symbols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "uuid": "23729711-44d9-49a9-9c10-8d238be308cb"
   },
   "outputs": [],
   "source": [
    "data = raw[symbols]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "uuid": "2bd5a671-fb77-4c78-90d9-bef99c34af86"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/yves/miniconda3/envs/py4fi/lib/python3.6/site-packages/ipykernel_launcher.py:1: DeprecationWarning: \n",
      ".ix is deprecated. Please use\n",
      ".loc for label based indexing or\n",
      ".iloc for positional indexing\n",
      "\n",
      "See the documentation here:\n",
      "http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1c204696d8>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAeoAAAEzCAYAAAD+XEDdAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nY4wxHmaJ2hhjjPGw/weU4U/DNdxCSgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c20425f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "(data / data.ix[0] * 100).plot(figsize=(8, 5), grid=True)\n",
    "# tag: portfolio_1\n",
    "# title: Stock prices over time\n",
    "# size: 90"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "uuid": "e7e3d4af-6b03-4b05-9bb2-69132aa9b96d"
   },
   "outputs": [],
   "source": [
    "rets = np.log(data / data.shift(1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "uuid": "3416c8ac-7ee5-4c5d-a929-92aa2881382d"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AAPL.O    0.218633\n",
       "MSFT.O    0.126401\n",
       "AMZN.O    0.269869\n",
       "GDX      -0.096212\n",
       "GLD       0.012069\n",
       "dtype: float64"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rets.mean() * 252"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "uuid": "437bb447-a4b0-4ddc-97de-965d2cb6c9f2"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AAPL.O</th>\n",
       "      <th>MSFT.O</th>\n",
       "      <th>AMZN.O</th>\n",
       "      <th>GDX</th>\n",
       "      <th>GLD</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAPL.O</th>\n",
       "      <td>0.064899</td>\n",
       "      <td>0.022504</td>\n",
       "      <td>0.026932</td>\n",
       "      <td>0.014669</td>\n",
       "      <td>0.001510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSFT.O</th>\n",
       "      <td>0.022504</td>\n",
       "      <td>0.050234</td>\n",
       "      <td>0.029146</td>\n",
       "      <td>0.010995</td>\n",
       "      <td>-0.000426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN.O</th>\n",
       "      <td>0.026932</td>\n",
       "      <td>0.029146</td>\n",
       "      <td>0.097792</td>\n",
       "      <td>0.009917</td>\n",
       "      <td>-0.001584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GDX</th>\n",
       "      <td>0.014669</td>\n",
       "      <td>0.010995</td>\n",
       "      <td>0.009917</td>\n",
       "      <td>0.150716</td>\n",
       "      <td>0.048760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GLD</th>\n",
       "      <td>0.001510</td>\n",
       "      <td>-0.000426</td>\n",
       "      <td>-0.001584</td>\n",
       "      <td>0.048760</td>\n",
       "      <td>0.027666</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          AAPL.O    MSFT.O    AMZN.O       GDX       GLD\n",
       "AAPL.O  0.064899  0.022504  0.026932  0.014669  0.001510\n",
       "MSFT.O  0.022504  0.050234  0.029146  0.010995 -0.000426\n",
       "AMZN.O  0.026932  0.029146  0.097792  0.009917 -0.001584\n",
       "GDX     0.014669  0.010995  0.009917  0.150716  0.048760\n",
       "GLD     0.001510 -0.000426 -0.001584  0.048760  0.027666"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rets.cov() * 252"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The Basic Theory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "uuid": "3d86ff5b-9de8-4cee-99ea-cc01e4697320"
   },
   "outputs": [],
   "source": [
    "weights = np.random.random(noa)\n",
    "weights /= np.sum(weights)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "uuid": "9d9499c0-c033-4d4a-b2d4-e8ef064eb9ae"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.0346395 ,  0.02726489,  0.2868883 ,  0.10396806,  0.54723926])"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "uuid": "c9ec5dc3-df96-4418-90fe-0e76ed7b006d"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.085043701982308262"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sum(rets.mean() * weights) * 252\n",
    "  # expected portfolio return"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "uuid": "40f68bdb-74ea-4f6d-9f93-c498a9a13167"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.024966990290115794"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.dot(weights.T, np.dot(rets.cov() * 252, weights))\n",
    "  # expected portfolio variance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "uuid": "351e317e-5f22-474b-b1a5-1f2934f608a1"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.15800946266004387"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sqrt(np.dot(weights.T, np.dot(rets.cov() * 252, weights)))\n",
    "  # expected portfolio standard deviation/volatility"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "uuid": "689bff52-80a9-48ac-9fce-0855e2a763ae"
   },
   "outputs": [],
   "source": [
    "prets = []\n",
    "pvols = []\n",
    "for p in range (2500):\n",
    "    weights = np.random.random(noa)\n",
    "    weights /= np.sum(weights)\n",
    "    prets.append(np.sum(rets.mean() * weights) * 252)\n",
    "    pvols.append(np.sqrt(np.dot(weights.T, \n",
    "                        np.dot(rets.cov() * 252, weights))))\n",
    "prets = np.array(prets)\n",
    "pvols = np.array(pvols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "uuid": "81d7f822-79e9-41bb-94b1-649807788f2e"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x1c20776828>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAfMAAAEMCAYAAADQy1+HAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nlLkgCIIgdHD+H7MVHfqd67sfAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c204691d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 4))\n",
    "plt.scatter(pvols, prets, c=prets / pvols, marker='o')\n",
    "plt.grid(True)\n",
    "plt.xlabel('expected volatility')\n",
    "plt.ylabel('expected return')\n",
    "plt.colorbar(label='Sharpe ratio')\n",
    "# tag: portfolio_2\n",
    "# title: Expected return and volatility for different/random portfolio weights\n",
    "# size: 90"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Portfolio Optimizations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "uuid": "637b7c75-4c82-4eec-bf8e-2ff5516fd459"
   },
   "outputs": [],
   "source": [
    "def statistics(weights):\n",
    "    ''' Return portfolio statistics.\n",
    "    \n",
    "    Parameters\n",
    "    ==========\n",
    "    weights : array-like\n",
    "        weights for different securities in portfolio\n",
    "    \n",
    "    Returns\n",
    "    =======\n",
    "    pret : float\n",
    "        expected portfolio return\n",
    "    pvol : float\n",
    "        expected portfolio volatility\n",
    "    pret / pvol : float\n",
    "        Sharpe ratio for rf=0\n",
    "    '''\n",
    "    weights = np.array(weights)\n",
    "    pret = np.sum(rets.mean() * weights) * 252\n",
    "    pvol = np.sqrt(np.dot(weights.T, np.dot(rets.cov() * 252, weights)))\n",
    "    return np.array([pret, pvol, pret / pvol])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "uuid": "1fea02c0-d092-4a29-a9eb-2d4022985a62"
   },
   "outputs": [],
   "source": [
    "import scipy.optimize as sco"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "uuid": "0124792d-7b7f-4f7c-ac42-367681a7145f"
   },
   "outputs": [],
   "source": [
    "def min_func_sharpe(weights):\n",
    "    return -statistics(weights)[2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "uuid": "a634bb6a-ef2e-4a68-9414-b2e320b58296"
   },
   "outputs": [],
   "source": [
    "cons = ({'type': 'eq', 'fun': lambda x:  np.sum(x) - 1})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "uuid": "40e6c1b4-8fb8-4a8f-b2ba-36ffdaefc47b"
   },
   "outputs": [],
   "source": [
    "bnds = tuple((0, 1) for x in range(noa))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "uuid": "d689f1b3-c680-4a1e-865b-85a64b06c0f6"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.2, 0.2, 0.2, 0.2, 0.2]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "noa * [1. / noa,]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "uuid": "dda15397-398b-445e-be6a-11e7ed0e3c32"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 108 ms, sys: 2.52 ms, total: 111 ms\n",
      "Wall time: 110 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "opts = sco.minimize(min_func_sharpe, noa * [1. / noa,], method='SLSQP',\n",
    "                       bounds=bnds, constraints=cons)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "uuid": "ee237054-2af4-4879-97d1-0ee77d84d9a8"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "     fun: -1.0556617020534316\n",
       "     jac: array([  4.79519367e-05,  -6.97374344e-05,   5.30779362e-05,\n",
       "         8.51281390e-01,  -4.90382314e-04])\n",
       " message: 'Optimization terminated successfully.'\n",
       "    nfev: 49\n",
       "     nit: 7\n",
       "    njev: 7\n",
       "  status: 0\n",
       " success: True\n",
       "       x: array([ 0.47403303,  0.05035899,  0.39381481,  0.        ,  0.08179317])"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "opts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "uuid": "e0a821b0-a330-4979-bec2-a9e731f11656"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.474,  0.05 ,  0.394,  0.   ,  0.082])"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "opts['x'].round(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "uuid": "faae2c2f-382b-427b-9426-87085a339b76"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.217,  0.206,  1.056])"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "statistics(opts['x']).round(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "uuid": "8aefec36-2e2e-49ea-ab30-75ccbcaa2b22"
   },
   "outputs": [],
   "source": [
    "def min_func_variance(weights):\n",
    "    return statistics(weights)[1] ** 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "uuid": "f84ed951-5f9b-4ec7-bb7c-330994bdb0b9"
   },
   "outputs": [],
   "source": [
    "optv = sco.minimize(min_func_variance, noa * [1. / noa,], method='SLSQP',\n",
    "                       bounds=bnds, constraints=cons)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "uuid": "76321897-4b6e-4714-965a-79bdd489b846"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "     fun: 0.015978878561911988\n",
       "     jac: array([ 0.03154033,  0.03221243,  0.03183019,  0.06642421,  0.03195841])\n",
       " message: 'Optimization terminated successfully.'\n",
       "    nfev: 70\n",
       "     nit: 10\n",
       "    njev: 10\n",
       "  status: 0\n",
       " success: True\n",
       "       x: array([  1.20347102e-01,   2.30912816e-01,   7.01553015e-02,\n",
       "         2.68272275e-17,   5.78584780e-01])"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "optv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "uuid": "031a4259-ecec-4cf4-85cd-98515fe15a6c"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.12 ,  0.231,  0.07 ,  0.   ,  0.579])"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "optv['x'].round(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "uuid": "1859a17c-e501-4a6f-88ae-16b9cf10b308"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.081,  0.126,  0.644])"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "statistics(optv['x']).round(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Efficient Frontier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "uuid": "a49f6ebe-1552-400f-b97f-a26d1bd9fa2a"
   },
   "outputs": [],
   "source": [
    "cons = ({'type': 'eq', 'fun': lambda x:  statistics(x)[0] - tret},\n",
    "        {'type': 'eq', 'fun': lambda x:  np.sum(x) - 1})\n",
    "bnds = tuple((0, 1) for x in weights)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "uuid": "6ec20ed9-ec0d-4b86-bf1e-dbbcbd331b57"
   },
   "outputs": [],
   "source": [
    "def min_func_port(weights):\n",
    "    return statistics(weights)[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "uuid": "75433eba-18d3-416a-95a9-c404293ef495"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 4.87 s, sys: 25.5 ms, total: 4.89 s\n",
      "Wall time: 4.93 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "trets = np.linspace(0.0, 0.25, 50)\n",
    "tvols = []\n",
    "for tret in trets:\n",
    "    cons = ({'type': 'eq', 'fun': lambda x:  statistics(x)[0] - tret},\n",
    "            {'type': 'eq', 'fun': lambda x:  np.sum(x) - 1})\n",
    "    res = sco.minimize(min_func_port, noa * [1. / noa,], method='SLSQP',\n",
    "                       bounds=bnds, constraints=cons)\n",
    "    tvols.append(res['fun'])\n",
    "tvols = np.array(tvols)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "uuid": "b16fdf94-8324-481a-a360-ed2060b9f481"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x1c208d00b8>"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAfMAAAEMCAYAAADQy1+HAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nZmbW4xzMzczMepyDuZmZWY/7F04iJNmQu1gaAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c20862668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 4))\n",
    "plt.scatter(pvols, prets,\n",
    "            c=prets / pvols, marker='o')\n",
    "            # random portfolio composition\n",
    "plt.scatter(tvols, trets,\n",
    "            c=trets / tvols, marker='x')\n",
    "            # efficient frontier\n",
    "plt.plot(statistics(opts['x'])[1], statistics(opts['x'])[0],\n",
    "         'r*', markersize=15.0)\n",
    "            # portfolio with highest Sharpe ratio\n",
    "plt.plot(statistics(optv['x'])[1], statistics(optv['x'])[0],\n",
    "         'y*', markersize=15.0)\n",
    "            # minimum variance portfolio\n",
    "plt.grid(True)\n",
    "plt.xlabel('expected volatility')\n",
    "plt.ylabel('expected return')\n",
    "plt.colorbar(label='Sharpe ratio')\n",
    "# tag: portfolio_3\n",
    "# title: Minimum risk portfolios for given return level (crosses)\n",
    "# size: 90"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Capital Market Line"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "uuid": "b6eb023a-2407-49d7-986d-3d47e9c3ae45"
   },
   "outputs": [],
   "source": [
    "import scipy.interpolate as sci"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {
    "uuid": "cca0eb49-0c77-4186-a2df-06ebf56fa923"
   },
   "outputs": [],
   "source": [
    "ind = np.argmin(tvols)\n",
    "evols = tvols[ind:]\n",
    "erets = trets[ind:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {
    "uuid": "c3bf6d9e-0548-4874-90fc-0555f05afd5e"
   },
   "outputs": [],
   "source": [
    "tck = sci.splrep(evols, erets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "uuid": "f37d6e01-0091-42d4-a9ca-1102f0fdb436"
   },
   "outputs": [],
   "source": [
    "def f(x):\n",
    "    ''' Efficient frontier function (splines approximation). '''\n",
    "    return sci.splev(x, tck, der=0)\n",
    "def df(x):\n",
    "    ''' First derivative of efficient frontier function. '''\n",
    "    return sci.splev(x, tck, der=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "uuid": "e0a3d820-a9f1-41fa-a5bf-46fe176fdb68"
   },
   "outputs": [],
   "source": [
    "def equations(p, rf=0.01):\n",
    "    eq1 = rf - p[0]\n",
    "    eq2 = rf + p[1] * p[2] - f(p[2])\n",
    "    eq3 = p[1] - df(p[2])\n",
    "    return eq1, eq2, eq3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "uuid": "2c23eced-0b5a-45cd-b677-f4eff5876f43"
   },
   "outputs": [],
   "source": [
    "opt = sco.fsolve(equations, [0.01, 0.5, 0.15])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "uuid": "f4c2c1e9-aef7-4d22-9e1c-3b7ff5066830"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.01      ,  1.0090905 ,  0.22552992])"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "opt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "uuid": "3651a6fa-7740-43fe-a18a-1134cbed7b0a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0., -0., -0.])"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.round(equations(opt), 6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "uuid": "b4e45542-14a5-4e96-9bbe-186873d9f429"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x1c209f1860>"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAfMAAAEMCAYAAADQy1+HAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nKzgnczMzs4JzMjczMys4J3MzM7OC+z8TlGasTSWhiQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1c208ec9b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 4))\n",
    "plt.scatter(pvols, prets,\n",
    "            c=(prets - 0.01) / pvols, marker='o')\n",
    "            # random portfolio composition\n",
    "plt.plot(evols, erets, 'g', lw=4.0)\n",
    "            # efficient frontier\n",
    "cx = np.linspace(0.0, 0.3)\n",
    "plt.plot(cx, opt[0] + opt[1] * cx, lw=1.5)\n",
    "            # capital market line\n",
    "plt.plot(opt[2], f(opt[2]), 'r*', markersize=15.0) \n",
    "plt.grid(True)\n",
    "plt.axhline(0, color='k', ls='--', lw=2.0)\n",
    "plt.axvline(0, color='k', ls='--', lw=2.0)\n",
    "plt.xlabel('expected volatility')\n",
    "plt.ylabel('expected return')\n",
    "plt.colorbar(label='Sharpe ratio')\n",
    "# tag: portfolio_4\n",
    "# title: Capital market line and tangency portfolio (star) for risk-free rate of 1%\n",
    "# size: 90"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "uuid": "f2e04c2a-434a-442d-bce2-0f7be60c6e80"
   },
   "outputs": [],
   "source": [
    "cons = ({'type': 'eq', 'fun': lambda x:  statistics(x)[0] - f(opt[2])},\n",
    "        {'type': 'eq', 'fun': lambda x:  np.sum(x) - 1})\n",
    "res = sco.minimize(min_func_port, noa * [1. / noa,], method='SLSQP',\n",
    "                       bounds=bnds, constraints=cons)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "uuid": "78362c70-0acf-4f13-9a7d-04adbc7de43a"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.525,  0.025,  0.443,  0.   ,  0.007])"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res['x'].round(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"http://hilpisch.com/tpq_logo.png\" alt=\"The Python Quants\" width=\"35%\" align=\"right\" border=\"0\"><br>\n",
    "\n",
    "<a href=\"http://tpq.io\" target=\"_blank\">http://tpq.io</a> | <a href=\"http://twitter.com/dyjh\" target=\"_blank\">@dyjh</a> | <a href=\"mailto:training@tpq.io\">training@tpq.io</a>\n",
    "\n",
    "**Quant Platform** |\n",
    "<a href=\"http://quant-platform.com\">http://quant-platform.com</a>\n",
    "\n",
    "**Python for Finance** |\n",
    "<a href=\"http://python-for-finance.com\" target=\"_blank\">Python for Finance @ O'Reilly</a>\n",
    "\n",
    "**Derivatives Analytics with Python** |\n",
    "<a href=\"http://derivatives-analytics-with-python.com\" target=\"_blank\">Derivatives Analytics @ Wiley Finance</a>\n",
    "\n",
    "**Listed Volatility and Variance Derivatives** |\n",
    "<a href=\"http://lvvd.tpq.io\" target=\"_blank\">Listed VV Derivatives @ Wiley Finance</a>\n",
    "\n",
    "**Python Training** |\n",
    "<a href=\"http://training.tpq.io\" target=\"_blank\">Python for Finance University Certificate</a>"
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
